What Data Science Positions Jobs are in India?

Data Science Supervisor
Headquartered in Dublin, Ohio, Cardinal Health, Inc. (NYSE: CAH) is a global, integrated healthcare services and products company connecting patients, providers, payers, pharmacists and manufacturers for integrated care coordination and better patient management. Backed by nearly 100 years of experience, with more than 50,000 employees in nearly 60 countries, Cardinal Health ranks among the top 20 on the Fortune 500.
Department Overview
AI & Data Science team builds analytics and artificial intelligence solutions that drive success for Cardinal Health by creating material savings, efficiencies and revenue growth opportunities. The team drives business innovation by leveraging emerging technologies and turning them into differentiating business capabilities.
Job Overview
The primary role of the Data Science Supervisor is to oversee the post-deployment operations, continuous optimization, and operational performance of Agentic AI and Intelligent Automation solutions within the Finance Digital Solutions portfolio. This role will lead the operational "Run" phase, ensuring that generative AI agents, Large Language Model (LLM) integrations, and production workflows remain highly available, secure, and accurate. This position collaborates closely with offshore/onshore developers, data scientists, and business partners to manage risk, solve complex problems, and deliver long-term support for mission-critical solutions.
**Responsibilities**
+ Lead the ongoing operations, maintenance, and performance evaluation of production Agentic AI engines, FastAPI/Flask services, and Python-based analytical pipelines.
+ Ensure production databases and connections to enterprise systems (such as SAP, Salesforce, and Postgres) are maintained, secure, and highly optimized.
+ Establish best practices for Agent Observation, Evaluation, and prompt maintenance to adapt to shifting financial processes and business rules.
+ Work with cross-functional partners across our highly matrixed organization to understand both upstream inputs to, and downstream impact of, current and future operational processes.
+ Align technical specifications and post-deployment modifications with business needs and enterprise security standard guidelines.
+ Act as a techno-functional leader, generating ideas for process and platform improvements and ensuring data compliance standards are met.
+ Provides direct supervision and leadership to team
+ Strategize and prioritize responsibilities of direct reports
+ Assess business opportunities and promote use of data science, analytics within domain and build internal and external resources and expertise.
+ A part of the role also requires to be hands-on and working together with external and internal partners to develop, test and operationalize data science and analytical solutions as well as ensure its adoption by businesses.
+ Work to leverage data (Transactional / Big Data, External/ Internal Data, Structured/ Unstructured Data) and analytics methods to develop analytics solutions
**_Qualifications_**
+ 6 - 8 years of AI & data science experience preferred, including 2-3 years of direct people management experience (direct people reporting)
+ BTech-BE from Tier 1/2 engineering schools or MStat/MS (Math)/MA Econ/ MS Analytics/data science from Tier 1/2 schools
+ Deep expertise in Google Cloud Platform (GCP) technologies, including Cloud SQL, BigQuery, and GCP Cloud Functions.
+ Advanced proficiency in Python (specifically FastAPI, Flask) and SQL.
+ Direct experience with Agentic AI architectures, Prompt Engineering, Agent Evaluation, and Agent Observation.
+ Strong knowledge of containerization and orchestration using Kubernetes.
+ Experience integrating and maintaining connections to enterprise databases and applications like Postgres, SAP, and Salesforce.
+ Design ML/LLM pipelines, good knowledge of RAG, prompt engineering.
+ Monitor system performance, logs, retrieval quality and prompt-effectiveness
+ Integrate microservices with ApigeeX for API management, security (authentication, authorization, rate limiting), monitoring, and analytics.
+ Skills in areas like Agentic AI, GenAI, and some other traditional AI techniques like optimization, Statistics, Machine learning, NLP, Image/ Video, Speech analytics
+ Preferably good knowledge of Agile & SCRUM development processes
**_Soft Skills_**
+ Coach and Mentor data science operations Team members
+ Excellent communication and storytelling skills (oral, written and presentation)
+ Highly driven, energetic, flexible & ability to multitask
+ Ability to work with teams/ stakeholders to drive change/ adoption of analytics solutions
_Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply._
_Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal_ _Opportunity/Affirmative_ _Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law._
_To read and review this privacy notice click_ here (

**Overview**
Come build community, explore your passions and do your best work at Microsoft with thousands of University interns from every corner of the world. This opportunity will allow you to bring your aspirations, talent, potential-and excitement for the journey ahead.
As a Data Scientist Intern at Microsoft, you will use machine learning, statistics, experiments, and more to build and improve great products while making business impact. As a Data Scientist intern you will collaborate with stakeholders, formulate approaches to solve problems and use algorithms and data sources in the context of business and engineering needs. You will also be able to combine your engineering abilities with analytical skills to make customer experiences better. Our Data Scientists use innovative methods, algorithms and tools daily to drive results throughout Microsoft devices, operating systems, products, and services and provide novel insights into business and customer scenarios.
At Microsoft, Interns work on real-world projects in collaboration with teams across the world, while having fun along the way. You'll be empowered to build community, explore your passions and achieve your goals. This is your chance to bring your solutions and ideas to life while working on cutting-edge technology.
**Responsibilities**
+ Formulate approaches to solve problems using well defined algorithms and data sources
+ Incorporate an understanding of product functionality and customer perspective to provide context for those problems.
+ Use data exploration techniques to discover new questions or opportunities within your problem area and propose applicability and limitations of the data.
+ Interpret the results of their analysis, validate their approach, and learn to monitor, analyze, and iterate to continuously improve.
+ Engage with peer stakeholders to produce clear, compelling, actionable insights that influence product and service improvements that will impact millions of customers.
+ Participate in the peer review process and act on feedback while learning innovative methods, algorithms, and tools to increase the impact and applicability of your results.
**Qualifications**
**Required Qualifications:**
+ Currently pursuing a Doctorate Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field.
+ Must have at least one additional quarter/semester of school remaining following the completion of the internship.
**Preferred Qualifications:**
+ Currently pursuing a Master's in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations. (

**What you'll do:**
Eaton Corporation's Center for Intelligent Power has an opening for a Data Scientist who is passionate about his or her craft. The Data Science Engineer will be involved in the design and development of ML/AI algorithms to solve power management problems. In addition to developing these algoriths, the Data Science Engineer will also be involved in successful integration of algorithms in edge or cloud systems using CI/CD and software release process.
- The candidate will demonstrate exceptional impact in delivering projects in terms of architecture, technical deliverables and project delivery throughout the project lifecycle. The candidate is expected to be conversant with Agile methodologies and tools.
- Experience on data analysis, ML/AI model development and related development environment that enables ML/AI algorithms for use on various processors or systems
- Work with a team of experts in deep learning, machine learning, distributed systems, program management, and product teams, and work on all aspects of design, development and delivery of end-to-end pipelines and solutions.
- Development of technical solutions and implement architectures for project and products along with data engineering and data science teams.
- Participate in architecture, design, and development of new intelligent power technology products and production quality end to end systems.
**Qualifications:**
- Master's Degree in Data Science
- 2+ years of progressive experience in delivering technology solutions in a production environment
- 2+ years of practical data science experience in the application of statistics, machine learning, and analytic approaches with a proven track record of solving critical business problems and uncovering new business opportunities
- 2 years working with customers (internal and external) on developing requirements and working as a solutions architect to deliver"
**Skills:**
+ Good Statistical background such as Bayesian networks, hypothesis testing, etc.
+ Hands on development of Deep learning and Machine learning models for Engineering applications like electrical/electronic systems, energy systems, data centers, mechanical systems
+ Hands on experinece on ML/DL models such as time series modeling, anomaly detection, root cause analysis, diagnostics, prognostics, pattern detection, data mining, etc.
+ Progamming Knowledge - Python, R, Matlab, C/C++, Java, PySpark, SparkR
+ Azure ML Pipeline, Databricks, MLFlow
+ Hands on optimization techniques like dynamic programming, particle swarm optimization, etc.
+ SW Development life-cycle process & tools Agile development methodologies and concepts including handson with Jira, bitbucket and confluence.
+ Knowledge on Computer Vision, Natural Language Processing, Recommendation AI Systems
+ Knowledge on traditional and new data analysis methods that can build statistical models and discover patterns in data
+ Knowledge on open source projects like Open CV, Gstreamer, OpenVINO, ONNX, Tensor flow, Pytorch and Caffe, MLOps Knowledge
+ Knowledge on Tensor Flow, Scikit, Keras, Spark ML, Numpy, Pandas
+ Knowledge of IoT technologies, including cloud processing, like Azure IoT Hub.
+ Knowledge of Scala"
+ Excellent verbal and written communication skills including the ability to effectively communicate technical concepts as a part of virtual, global teams
+ Ablity to understand academic research and apply new data science techniques
+ Experience being part of larger teams with established big data platform practices, as well as smaller teams where they made a bigger impact in terms of scope.
+ Experience of working with global teams work Experience and awareness, Strong communication skills to interact with global teams.
+ Self-directed and hungry to learn - a person, who with time in his/her hands, will independently find interesting ways to push the envelope, learning new skills and growing Self and the team.

**Role : AIML Data Science**
**Location : Pan India**
**Experience : 4 to 12 Years**
**Relevant Exp : 2+ Years**
**Notice Period : Immediate to 90 days**
**Job Description:**
1. Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges
a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem
b. Improve Model accuracy to deliver greater business impact
c. Estimate business impact due to deployment of model
2. Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge
3. Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development - Python / R / SQL / Cloud data pipelines
4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch
5. Experience in using Deep learning models with text, speech, image and video data
a. Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc
b. Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV
c. Knowledge of State of the art Deep learning algorithms
6. Optimize and tune Deep Learnings model for best possible accuracy
7. Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau
8. Work with application teams, in deploying models on cloud as a service or on-prem
a. Deployment of models in Test / Control framework for tracking
b. Build CI/CD pipelines for ML model deployment
9. Integrating AI&ML models with other applications using REST APIs and other connector technologies
10. Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.
· Technology/Subject Matter Expertise
· Sufficient expertise in machine learning, mathematical and statistical sciences
· Use of versioning & Collaborative tools like Git / Github
· Good understanding of landscape of AI solutions - cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
· Develop prototype level ideas into a solution that can scale to industrial grade strength
· Ability to quantify & estimate the impact of ML models
· **Softskills Profile**
+ Curiosity to think in fresh and unique ways with the intent of breaking new ground.
+ Must have the ability to share, explain and "sell" their thoughts, processes, ideas and opinions, even outside their own span of control
+ Ability to think ahead, and anticipate the needs for solving the problem will be important
· Ability to communicate key messages effectively, and articulate strong opinions in large forums
· **Desirable Experience:**
· Keen contributor to open source communities, and communities like Kaggle
· Ability to process Huge amount of Data using Pyspark/Hadoop
· Development & Application of Reinforcement Learning
· Knowledge of Optimization/Genetic Algorithms
· Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios
· Optimize and tune deep learning model for best possible accuracy
· Understanding of stream data processing, RPA, edge computing, AR/VR etc
· Appreciation of digital ethics, data privacy will be important
· Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus
· Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus
Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.

**Job Description Summary**
As an AI Engineer / Data Science Specialist, you will be part of an AI-enabled Systems Engineering organization focused on transforming healthcare product development through Artificial Intelligence, Machine Learning, Data Science, and Generative AI technologies.
You will work on large-scale engineering, quality, and product lifecycle datasets to develop intelligent solutions that improve engineering productivity, product quality, regulatory compliance, and patient outcomes. Working alongside Systems Engineers, AI Scientists, Software Engineers, Verification & Validation Engineers, and Domain Experts, you will help build the next generation of AI-powered engineering workflows and healthcare technologies.
GE HealthCare is a leading global medical technology and digital solutions innovator. Our purpose is to create a world where healthcare has no limits. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference helps build a healthier world.
tex
**Job Description**
**Roles & Responsibilities**
+ Develop AI, machine learning, and analytics solutions to address engineering and business challenges.
+ Collaborate with Systems Engineers, Software Engineers, and Verification Engineers to create AI-driven engineering productivity tools and workflows.
+ Analyze structured and unstructured datasets from requirements, defects, test results, quality systems, documentation, and operational processes.
+ Perform exploratory data analysis, statistical analysis, and feature engineering on complex datasets.
+ Build, evaluate, and deploy machine learning models for predictive, descriptive, and generative AI use cases.
+ Develop Retrieval-Augmented Generation (RAG), Agentic AI, and LLM-based applications for engineering knowledge management and workflow automation.
+ Participate in data preparation, cleansing, validation, and quality assessment activities.
+ Create dashboards, visualizations, reports, and technical documentation to communicate findings and model performance.
+ Contribute to responsible AI practices, model governance, traceability, and validation processes.
+ Stay current with emerging AI technologies and identify opportunities to apply them to healthcare engineering problems.
+ Support prototype development, experimentation, and proof-of-concept activities for future AI-enabled engineering capabilities.
**Required Qualifications**
+ Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Engineering, or another STEM discipline.
+ 0-2 years of experience in AI, Data Science, Software Engineering, Analytics, or related fields.
+ Strong programming skills in Python.
+ Proficiency in Python and common data science, machine learning, and AI frameworks (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or equivalent).
+ Exposure to Generative AI and LLM frameworks such as LangChain, LlamaIndex, Semantic Kernel, OpenAI / Azure OpenAI APIs
+ Understanding of:
+ Machine Learning fundamentals
+ Statistics and probability
+ Data structures and algorithms
+ Model evaluation techniques
+ Knowledge of SQL and data manipulation techniques.
+ Strong analytical and problem-solving skills.
+ Effective written and verbal communication skills.
+ Ability to work in a collaborative, cross-functional environment.
+ Passion for innovation, continuous learning, and solving real-world problems using AI.
**Preferred Qualifications**
+ Internship or project experience in AI, Machine Learning, Data Science, or Software Development.
+ Knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Agentic AI concepts.
+ Familiarity with cloud platforms such as Azure, AWS, or GCP.
+ Experience with version control (Git) and software development practices.
+ Exposure to healthcare, medical devices, quality systems, or regulated environments.
+ Experience working with large-scale structured and unstructured data.
+ Familiarity with data visualization tools such as Power BI, Tableau, or equivalent.

**Job Description Summary**
The Data Science Specialist will develop and implement Artificial Intelligence based solutions across various disciplines in GE Aerospace. In this role, the candidate will contribute to the development and deployment of modern machine learning, artificial intelligence, statistical methods, operations research, semantic analysis etc. for finding structure in large data sets. The candidate will be responsible for executing data science projects under limited guidance from senior members to deliver business outcomes. This role requires a good technical background, strong problem-solving skills, and the ability to work collaboratively with stakeholders from different functional and business teams.
**Job Description**
Site Overview
Established in 2000, the John F. Welch Technology Center (JFWTC) in Bengaluru is our multidisciplinary research and engineering center. Engineers and scientists at JFWTC have contributed to hundreds of aviation patents, pioneering breakthroughs in engine technologies, advanced materials, and additive manufacturing.
Role Overview
+ Understand business problems and implement Data Science solutions.
+ Design, develop, and implement machine learning and artificial intelligence models and algorithms.
+ Understand various business processes pertaining to Analytics Development Process
+ Collect, preprocess, and analyze large datasets to be used for training and testing machine learning models.
+ Ensure data quality and integrity throughout the data pipeline.
+ Conduct experiments to develop model and evaluate model performance and iterate on model improvements.
+ Under the guidance of senior members, work with Data Engineering teams to deploy data science models into production environments.
+ Monitor and maintain deployed models to ensure they perform as expected.
+ Under the guidance of senior members, work closely with data architects, data engineers, and other stakeholders to understand business requirements and translate them into technical solutions.
+ Optimize machine learning models for performance, scalability, and efficiency.
+ Be aware of latest advancements in machine learning and artificial intelligence.
+ Explore and implement new machine learning and artificial intelligence techniques and tools to enhance the team's capabilities.
+ Maintain comprehensive documentation of machine learning models, algorithms, and processes.
The Ideal Candidate
+ The ideal candidate should have experience in Gen AI/LLM, python and SQL.
Required Qualifications:
+ Master's or PhD degree in Statistics, Machine Learning, Computer Science or related STEM fields (Science, Technology, Engineering and Math) with analytics development experience
+ Proficiency in Python and SQL (mandatory).
+ Familiarity with Python web frameworks.
+ Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine learning services
+ Awareness of Knowledge Graphs
+ Utilize Docker for containerization of application services.
+ Implement and maintain CI/CD pipelines (e.g., GitHub Actions, AWS CodeBuild/CodePipeline) and use Git for version control.
+ Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on datasets
+ Demonstrated skill at data visualization and storytelling for an audience of stakeholders
Preferred Qualifications:
+ Influences within peer group.
+ Implements specific component(s) of the roadmap.
+ Evaluates features using well known or prescribed recipes and appropriately down selects to valuable ones.
+ Aware of models such as CART / SVM / RF / Neural Net and the associated sub-models
+ Knowledge on Gen AI/LLM
+ Uses Cross Validation and other Verification & Validation techniques to build robust models from large data sets.
+ Understands the types of issues that impact data quality
+ Performs basic data cleaning operations such as flagging missing and invalid data etc.
+ Fits normal parameters to data and assess goodness of fit
+ Can use and interpret t-tests, ANOVA and basic hypothesis testing with good utilization of p-values.
+ Codes using modular practices for reusage and object-oriented Effectively shows visualization of data exploration using box, bubble and matrix plots.
+ Has a basic understanding of GE Aerospace business and how the tools they are developing create value.
At GE Aerospace, we have a relentless dedication to the future of safe and more sustainable flight and believe in our talented people to make it happen. Here, you will have the opportunity to work on really cool things with really smart and collaborative people. Together, we will mobilize a new era of growth in aerospace and defense. Where others stop, we accelerate.
**Additional Information**
**Relocation Assistance Provided:** Yes
GE Aerospace is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

**HOW MIGHT YOU DEFY IMAGINATION?**
If you feel like you're part of something bigger, it's because you are. At Amgen, our shared mission-to serve patients-drives all that we do. We are global collaborators who achieve together-researching, manufacturing, and delivering ever-better products that reach millions of patients worldwide. It's time for a career you can be proud of.
**Role Overview**
The Associate Data Scientist is an entry-level role supporting data science initiatives across Amgen's portfolio. This role will work closely with Data Science Leads and senior team members to contribute to analytics, modeling, and insight generation, while building strong foundations in applied data science.
**Live | What you will do**
+ Support **analytics and data science projects** across commercial use cases in the Gen Med portfolio
+ Assist in **data preparation, exploratory analysis, and feature engineering** to enable modeling efforts
+ Contribute to development and testing of **predictive models and analytical frameworks** under guidance of senior data scientists
+ Perform **metric tracking, performance analysis, and validation checks** with high attention to detail
+ Support creation of **insight summaries, visualizations, and presentations** for business stakeholders
+ Maintain and update **code, dashboards, and analytical assets** in Python/SQL environments
+ Follow best practices for **documentation, QA, and reproducibility**
+ Collaborate with team members to meet project timelines and communicate progress effectively
+ Engage in continuous learning across **predictive modeling, experimentation, and commercial analytics methods**
**Thrive | What you can expect**
+ Structured learning and hands-on experience in **commercial data science applications**
+ Exposure to **end-to-end analytics delivery across brands and use cases**
+ Mentorship from experienced data scientists and opportunities to grow into **independent contributors**
+ A collaborative environment focused on **learning, impact, and development**
**Basic Qualifications**
+ Bachelor's or Master's degree in Data Science, Statistics, Engineering, or a related quantitative field
+ 3 years of experience in **analytics, data science, or related roles**
+ Working knowledge of **Python and SQL**
+ Strong analytical thinking and problem-solving skills
+ Attention to detail and ability to deliver **high-quality, accurate work**
**Preferred Qualifications**
+ Exposure to **predictive modeling, experimentation, or statistical analysis**
+ Familiarity with **commercial analytics or marketing performance measurement**
+ Interest in **healthcare, pharma, or life sciences analytics**
+ Experience with tools such as **Jupyter notebooks, Git, or data visualization platforms**
+ Ability to work collaboratively with **cross-functional teams and senior stakeholders**
+ Strong communication skills and willingness to learn in a fast-paced environment

**Meet the Team:**
The AutoQuote team at Cisco builds and operates the automated quoting platform that powers Cisco's global renewals business. Our mission is to generate accurate, ready-to-order quotes at scale - minimizing manual effort for partners and distributors, reducing booking friction, and driving simplification across Cisco's renewal workflows.
We are a product engineering team running a homegrown, cloud-native application hosted on GCP. Our stack is built on a microservices architecture orchestrated with Kubernetes, with Prefect managing our data and workflow pipelines, and Pub/Sub and REST APIs handling communication across services. We move fast, operate at scale, and are actively integrating AI capabilities into the core of what we build.
**Your Impact:**
We are seeking an experienced technical leader to serve as Leader, Data Science on the AutoQuote team at Cisco. This is a principal-level engineering and technical leadership role responsible for driving the architecture, AI strategy, and engineering direction of AutoQuote's cloud-native software platform. The ideal candidate brings deep software engineering expertise, a track record of leading complex technical initiatives, and the technical authority to elevate the team around them.
AI fluency is a non-negotiable expectation of this role - not just personal proficiency, but the ability to actively drive AI adoption across the team, govern its use responsibly, and continuously push the boundaries of what AI-assisted engineering can deliver. This leader will set the technical tone for how the AutoQuote engineering organization builds.
**What You'll do:**
- Own the technical architecture and engineering strategy for AutoQuote's cloud-native platform - spanning AI feature integration, data pipeline infrastructure, microservices design, and platform reliability.
- Lead the design and delivery of the highest-complexity, highest-impact engineering initiatives on the team, setting the architectural patterns and engineering standards that guide the broader organization.
- Define and enforce software quality standards, AI usage guidelines, and engineering best practices across the AutoQuote engineering organization.
- Partner with engineering leadership, product management, and program stakeholders to translate program strategy into a coherent technical roadmap and prioritized backlog.
- Evaluate, prototype, and champion emerging AI capabilities - including LLM integration, agentic frameworks, and AI-assisted development tooling - driving adoption across the team and into the product.
- Drive responsible AI governance across AutoQuote, including prompt engineering standards, AI output evaluation practices, and compliance with Cisco security and data handling policies.
- Mentor and technically develop senior and mid-level engineers; serve as the primary technical authority and critical issue point for complex engineering decisions.
- Lead architecture reviews, critical design decisions, and cross-functional technical alignment sessions.
- Represent AutoQuote engineering in program-level and executive forums; communicate technical tradeoffs, risks, and decisions with clarity to both technical and non-technical audiences.
**Minimum Qualifications:**
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field; advanced degree preferred.
- 8+ years of professional software engineering experience, with a demonstrated track record at the principal, staff, or distinguished engineer level.
- Deep proficiency in Python; demonstrated ability to architect polyglot, cloud-native solutions - technology selection should always be driven by what is right for the problem, not a single prescribed stack.
- Proven expertise in cloud-native architecture on GCP and/or AWS, including Kubernetes, distributed systems, managed AI/ML services, and data pipeline infrastructure.
- Extensive hands-on experience applying AI/ML services and frameworks (LLM APIs, LangChain, cloud-managed AI services) in production engineering environments.
- Demonstrated mastery of LLMs as engineering tools - prompt engineering, AI-assisted development, model output evaluation, and designing AI-powered workflows and agentic systems.
- Track record of setting technical standards, driving architecture decisions at a program or organization level, and leading cross-functional engineering initiatives.
- Strong technical communication skills - able to write crisp technical proposals, represent engineering tradeoffs to executive stakeholders, and influence without direct authority.
- Experience operating and improving high-availability production systems at enterprise scale.
**Preferred Qualifications:**
- Experience designing and delivering agentic AI systems or multi-agent orchestration frameworks in a production engineering environment.
- Cloud or AI certifications at the professional or specialization level (GCP Professional, AWS Professional, or equivalent).
- Prior experience in a staff, principal, or distinguished engineering role within a large-scale product engineering organization.
- Familiarity with enterprise AI governance, responsible AI frameworks, or model evaluation and monitoring practices.
ADDITIONAL INFORMATION
- This role operates at the principal engineer level - deep technical authority combined with leadership through influence across the AutoQuote engineering organization.
- Strong AI mastery is a non-negotiable expectation: the candidate should be actively pushing the state of AI-assisted development on the team and within the broader organization.
- The candidate will work closely with program and engineering leadership and is expected to represent technical decisions and tradeoffs clearly to non-technical audiences.
- All work is conducted in alignment to Cisco security policy and compliance requirements, including responsible handling of data and AI-generated content.
**Why Cisco?**
At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
Cisco is an Affirmative Action and Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis.
Cisco will consider for employment, on a case by case basis, qualified applicants with arrest and conviction records.

**Data Science Analyst**
**Job Objective**
We are seeking a data-driven and analytically minded professional to join the Data Science and AI Engineering team within International Health, Cigna Healthcare. Our team designs and delivers high-impact descriptive, predictive, and emerging AI-enabled analytics to address complex challenges across global and local healthcare markets.
This role is primarily aligned to the Provider domain, supporting insights related to healthcare providers such as hospitals, physician groups, and ancillary care organizations, and their interaction with health insurance operations. The position will also collaborate closely with adjacent domains, like Clinical and Payment Integrity, to ensure analytics are grounded in clinical relevance, operational efficiency, and value-based care outcomes.
This is an opportunity for a data analyst to demonstrate strong technical capability and business acumen by translating data into actionable insights and scalable data products that drive measurable value for healthcare and health insurance stakeholders.
**Job Responsibilities**
+ Work with Product Owners and domain stakeholders to understand provider-related business questions and contribute to the selection of appropriate analytical approaches
+ Assist in the development and implementation of predictive and prescriptive analytics, supporting use cases such as provider performance analysis, network insights, and care delivery optimization
+ Participate in an agile operating model, contributing to sprint activities, backlog items, and iterative delivery of analytics and data products within cross-functional teams
+ Support the use of generative AI-enabled analytics in a controlled and responsible manner, including contributing to knowledge bases that enable Retrieval‑Augmented Generation (RAG) for analytics and insight discovery
+ Contribute to the creation and maintenance of quality provider datasets by helping identify critical data elements (CDEs) and supporting data quality, consistency, and usability for analytics
+ Assist in tracking and communicating the business value and outcomes associated with analytics and data products
+ Collaborate with Data Engineering and Cloud Engineering teams to support data ingestion, enrichment, and availability across first- and third-party healthcare and provider data sources
+ Work with Data Governance and AI Governance teams to follow data protection, responsible AI practices, and EU AI Act-related requirements, building familiarity through practical application
**Requirements**
+ Tertiary education in Data Science, Statistics, Computer Science, Engineering, or a related discipline
+ Working knowledge of International Classification of Diseases (ICD) and its use in healthcare and health insurance analytics
+ Practical experience using Python for data analysis
+ Experience querying and working with SQL and NoSQL data stores
+ Exposure to cloud-based data and analytics platforms, preferably AWS and Databricks (e.g., SageMaker, Athena, or equivalent tools)
+ Basic to intermediate understanding of Foundation Models, including common use cases and limitations in enterprise settings
+ Some hands-on exposure to prompt engineering or agent-based approaches, supporting analytics or insight-generation workflows
+ Awareness and foundational knowledge of the EU AI Act, with interest or initial experience applying governance, transparency, or risk-related concepts in analytics or AI initiatives
+ Good communication skills in English, with the ability to explain analytical findings clearly to non-technical stakeholders; additional languages are an advantage
**About The Cigna Group**
Cigna Healthcare, a division of The Cigna Group, is an advocate for better health through every stage of life. We guide our customers through the health care system, empowering them with the information and insight they need to make the best choices for improving their health and vitality. Join us in driving growth and improving lives.