1229 Predictive Modeling jobs in Bangalore

Job Role : Data Scientist

Experience : 8 to 15 Years

Location : Bengaluru, Hyderabad, Chennai, Mumbai

Must Have :

• Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.
• Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.
• Machine Learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests.
• Deep Learning : CNN, RNN, LSTMs, GAN, VAEs etc.,
• Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques.
• Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description.
• Experience with Data Visualization Tools like matplotlib, ggplot, d3.Js., Tableau that help to visually encode data
• Preferred Experience with machine learning and GenAI algorithms such as large language models
• Prior experience working with Python or other programming languages.
• 1+ years of experience with cloud native engineering, AWS, Azure, Google

Who we are

Nirvana is on a mission to modernize commercial insurance and enable a safer world. Our technology platform delivers modern insurance & risk management to not only help our customers protect their businesses, but actually improve safety for everyone.

To start, we’re transforming the legacy, $750B+ commercial insurance industry through cutting-edge predictive models using real-time IoT data (~50B connected devices by 2030), automation to deliver instantaneous quotes & faster underwriting, & proactive, and data-driven insights to help customers prevent accidents.

Backed by top-tier VCs including General Catalyst & Lightspeed Ventures, Nirvana became the fastest insurtech EVER to launch in Jan 2022 and crossed >
$10M run rate in under 6months, more than 2x faster than best-in-class insurtechs. Our leadership team has helped scale multi-billion dollar companies from scratch including Samsara, Rubrik, Acko & Flexport, and includes industry veterans from Hiscox, AIG, The Hartford & RLI.

About the role

At Nirvana, we work with heterogeneous datasets and mine predictive signals to accurately identify risks for businesses. Some of the data we work with includes,

• 100s of millions of GPS and sensor data points per vehicle, ingested and stored in our proprietary data platform.
• Safety events like harsh braking, distracted driving, etc computed from sensors in commercial vehicles.
• High-dimensional datasets containing, among others, decades of vehicle inspection, crash, and violation data for all commercial vehicles in the US.

As a Senior Data Scientist, you will work closely with our data engineering and insurance teams and use these large datasets to help build data-driven insurance and safety products in a fast-paced startup environment. You must enjoy working with large data and finding interesting patterns in the data through analytics experiments in a methodical and data-driven scientific way.

The insurance / risk business has many unsolved problems where sophisticated use of information plays a critical role. Join us in making an impact on the industry!

What you’ll do

• Extract actionable insights and recommendations from time series data to help our customers improve their safety
• Work closely with the insurance team to build and validate complex risk models
• Standardizing analysis methodology and building automation frameworks
• Understand data characteristics, prepare and clean large high-dimensional data sets, and define and automate robust data quality measures
• Work in cross functional teams

About you

• Graduate degree in a quantitative or technical discipline and/or 5+ years of applying advanced quantitative techniques to problems in industry
• Strong demonstrable knowledge of topics such as statistical inference, predictive analytics, probability theory, machine learning, etc
• Strong technical (written and verbal) communication, prioritization, and time management skills
• Strong programming skills with experience using modern packages in R and Python
• Demonstrated experience building, validating, and applying statistical machine learning methods to real world problems

What you’ll get from us

• Competitive compensation & meaningful equity
• Health insurance for you and your family
• Monthly wellness stipend
• Hybrid culture and reimbursement for home office equipment
• A flexible vacation policy and a team that understands building a company is a marathon, not a sprint
• A culture that gives you the autonomy you need to do great work, and the transparency you need to make good decisions
• #LI_Hybrid

TE-4 Years and above

Location- Bangalore/Chennai/Hyderabad

NP- 15-30 Days max

JOB DESCRIPTION

Join our fast‑growing team to build a unified platform for data analytics, machine learning, and generative AI. You’ll integrate the AI/ML toolkit, real‑time streaming into a backed feature store, and dashboards—turning raw events into reliable features, insights, and user‑facing analytics at scale.

What you’ll do

• Design and build streaming data pipelines (exactly‑once or effectively‑once) from event sources into low‑latency feature serving and NRT and OLAP queries.
• Develop an AI/ML toolkit: reusable libraries, SDKs, and CLIs for data ingestion, feature engineering, model training, evaluation, and deployment.
• Stand up and optimize a production feature store (schemas, SCD handling, point‑in‑time correctness, TTL/compaction, backfills).
• Expose features and analytics via well‑designed APIs/Services;
  integrate with model serving and retrieval for ML/GenAI use cases.
• Build and operationalize Superset dashboards for monitoring data quality, pipeline health, feature drift, model performance, and business KPIs.
• Implement governance and reliability: data contracts, schema evolution, lineage, observability, alerting, and cost controls.
• Partner with UI/UX, data science, and backend teams to ship end‑to‑end workflows from data capture to real‑time inference and decisioning.
• Drive performance: benchmark and tune distributed DB (partitions, indexes, compression, merge settings), streaming frameworks, and query patterns.
• Automate with CI/CD, infrastructure‑as‑code, and reproducible environments for quick, safe releases.

Tech you may use

Languages: Python, Java/Scala, SQL

Streaming/Compute: Kafka (or Pulsar), Spark, Flink, Beam

Storage/OLAP: ClickHouse (primary), object storage (S3/GCS), Parquet/Iceberg/Delta

Orchestration/Workflow: Airflow, dbt (for transformations), Makefiles/Poetry/pipenv

ML/MLOps: MLflow/Weights & Biases, KServe/Seldon, Feast/custom feature store patterns, vector stores (optional)

Dashboards/BI: Superset (plugins, theming), Grafana for ops

Platform: Kubernetes, Docker, Terraform, GitHub Actions/GitLab CI, Prometheus/OpenTelemetry

Cloud: AWS/GCP/Azure

What we’re looking for

1. 4+ years building production data/ML or streaming systems with high TPS and large data volumes.
2. Strong coding skills in Python and one of Java/Scala;
   solid SQL and data modeling.
3. Hands‑on experience with Kafka (or similar), Spark/Flink, and OLAP stores—ideally ClickHouse.
4. GenAI pipelines: retrieval‑augmented generation (RAG), embeddings, prompt/tooling workflows, model evaluation at scale.
5. Proven experience designing feature pipelines with point‑in‑time correctness and backfills;
   understanding of online/offline consistency.
6. Experience instrumenting Superset dashboards tied to ClickHouse for operational and product analytics.
7. Fluency with CI/CD, containerization, Kubernetes, and infrastructure‑as‑code.
8. Solid grasp of distributed systems and architecture fundamentals: partitioning, consistency, idempotency, retries, batching vs. streaming, and cost/perf trade‑offs.
9. Excellent collaboration skills;
   ability to work cross‑functionally with DS/ML, product, and UI/UX.
10. Ability to pass a CodeSignal prescreen coding test.

Grid Dynamics (Nasdaq:GDYN) is a digital-native technology services provider that accelerates growth and bolsters competitive advantage for Fortune 1000 companies. Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization. Grid Dynamics achieves high speed-to-market, quality, and efficiency by using technology accelerators, an agile delivery culture, and its pool of global engineering talent. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the US, UK, Netherlands, Mexico, India, Central and Eastern Europe.

To learn more about Grid Dynamics, please visit . Follow us on Facebook , Twitter , and LinkedIn .

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Role Overview:

As a Machine Learning & Data Science Intern, you will work closely with our team to develop data-driven solutions, explore datasets, and apply ML techniques to real-world problems. This is a hands-on opportunity to learn, experiment, and contribute to building products that make a difference.

Key Responsibilities:

• Assist in collecting, cleaning, and analyzing large datasets.
• Implement and experiment with machine learning models and algorithms.
• Support in building predictive models, recommendation systems, or NLP applications.
• Visualize data and present insights to the team.
• Collaborate with engineers and product teams to integrate ML solutions.
• Stay updated with the latest research and ML techniques.

Requirements:

• Currently pursuing or recently completed a degree in Computer Science, Data Science, Statistics, or a related field.
• Basic understanding of machine learning algorithms, statistics, and data analysis.
• Familiarity with Python, R, or similar languages.
• Experience with ML libraries such as scikit-learn, TensorFlow, or PyTorch is a plus.
• Strong problem-solving skills and curiosity to learn.
• Good communication skills and ability to work in a collaborative environment.

What You'll Learn:

• Hands-on experience with real-world ML projects.
• End-to-end data science workflow, from data collection to model deployment.
• Exposure to working in a fast-paced startup environment.
• Collaborative teamwork and product-focused thinking.

Join us as a Data Science & Business Intelligence Platform Lead

• Were looking for someone who can influence and have organisational skills to lead us toagreed targets
• Are you ready to take on a role where your influence and organizational skills can truly shine? Join our dynamic Data Technology Platforms team within Data & Analytics and lead us to achieve our ambitious targets.
• Youll be delivering, owning and maintaining the platforms operational stability and performance technology
• We're offering this role at director level

What you'll do

In this exciting role, you'll own the remediation of technical issues and drive the simplification and improvement of our platform architecture and technology. You'll build the platform roadmap, collaborating with centres of excellence to ensure you have the right resources. Your expertise will optimize business solutions for our customers' needs and align with our overall technology strategy. On top of this, you'll . Youll be able to really make this role your own, allowing excellent exposure for you and your work.

Youll also be:

• Taking ownership of the financial, commercial and flow performance of the platform
• Managing the platform risk culture, making sure that teams effectively collaborate to mitigate risk
• Delivering the regulatory reporting and managing the relevant budgets provided
• Leading strategic initiatives, manage high-performing teams, and deliver scalable AI solutions in a regulated financial environment

The skills you'll need

In this role, youll need to have in-depth domain or platform product knowledge and experience. You should have at least 18 years of experience with considerable AI skills, including experience with machine learning, natural language processing, and AI-driven analytics and teams.

Youll also be expected to have:

• Knowledge and experience with AWS, Azure, and Google Cloud Provider
• Proven experience with GenAI (LLMs, prompt engineering)
• Business intelligence knowledge and experience of working in banking/financial insititution
• Strong AWS cloud and ML infrastructure skills
• Strong leadership skills, including Agile and servant leadership experience
• Architecture, design, and engineering skills relevant to the specific platform
• Experience working and running high-performance, large-scale Agile and non-Agile programs, projects, and teams

Data Science + Gen AI with below mandatory skills.

Must to Have : Agent Framework, RAG Framework, Chunking Strategies, LLMs, AI on cloud

Services, Open Source Frameworks like Langchain, Llama Index, Vector Database, Token

Management, Knowledge Graph, Vision

Exp Range - 4 to 6 years

Major Duties & Responsibilities

•  Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business

questions

•  Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment

and operationalization of projects

•  Influence machine learning strategy for Digital programs and projects

•  Make solution recommendations that appropriately balance speed to market and analytical soundness

•  Explore design options to assess efficiency and impact, develop approaches to improve robustness and rigor

•  Develop analytical / modelling solutions using a variety of commercial and open-source tools (e.g., Python, R,

TensorFlow)

•  Formulate model-based solutions by combining machine learning algorithms with other techniques such as simulations.

•  Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations,

scenarios, and stories.

•  Create algorithms to extract information from large, multiparametric data sets.

•  Deploy algorithms to production to identify actionable insights from large databases.

•  Compare results from various methodologies and recommend optimal techniques.

•  Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations,

scenarios, and stories.

•  Develop and embed automated processes for predictive model validation, deployment, and implementation

•  Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science

•  Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate

reusability, and reliability upon deployment

•  Lead discussions at peer review and use interpersonal skills to positively influence decision making

•  Provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts; make

impactful contributions to internal discussions on emerging practices

•  Facilitate cross-geography sharing of new ideas, learnings, and best-practices

Required Qualifications

•  Bachelor of Science or Bachelor of Engineering at a minimum.

•  4-6 years of work experience as a Data Scientist

•  A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to

quickly cycle hypothesis through the discovery phase of a project

•  Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL,

Hadoop/Hive, Scala)

•  Good hands-on skills in both feature engineering and hyperparameter optimization

•  Experience producing high-quality code, tests, documentation

•  Experience with Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Azure ML,

Synapse, Databricks

•  Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine

learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies

•  Proficiency in statistical concepts and ML algorithms

•  Good knowledge of Agile principles and process

•  Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team

•  Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and

results

•  Self-motivated and a proactive problem solver who can work independently and in teams

Work with one of the Big 4's in India

Tableau, SQL database, and Python (All are Mandatory)

EX :
5+ years

CTC –
Max 25 LPA

Location :
Bangalore

NP :
0 to 30 days

By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.

The Future Begins Here

At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the need of patients, our people, and the planet.

Bengaluru, the city, which is India's epicenter of Innovation, has been selected to be home to Takeda's recently launched Innovation Capability Center. We invite you to join our digital transformation journey. In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement.

At Takeda's ICC we Unite in Diversity

Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and abilities they bring to our company. We are continuously improving our collaborators journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team.

The Opportunity

As a Data Scientist, you will have the opportunity to apply your analytical skills and expertise to extract meaningful insights from vast amounts of data. We are currently seeking a talented and experienced individual to join our team and contribute to our data-driven decision-making process.

Objectives/Purpose: Emphasize the design, development, and deployment of AI/Gen AI models in production environments, along with a strong focus on data engineering and end-to-end architectural understanding.

Accountabilities:

• Data Engineering: Design and implement robust data pipelines and ETL processes to support AI/Gen AI model development and deployment.
• AI/Gen AI Model Deployment: Lead the deployment of AI/Gen AI models in production environments, ensuring scalability, reliability, and maintainability.
• End-to-End Architecture: Develop and maintain comprehensive architectural documentation, ensuring alignment with enterprise architecture principles.
• Compliance and Standards: Ensure all solutions comply with architectural, security, and privacy standards.
• Collaboration: Work closely with data scientists, data engineers, and other stakeholders to deliver high-quality AI solutions.
• Continuous Improvement: Establish and institutionalize regular reviews for solution adoption and continuous improvement.
• Continuously improve model performance by analyzing and refining model architectures and processes.
• Familiarity with containerization tools (e.g., Docker, Kubernetes) for deploying models.
• Experience with model monitoring and performance tracking in production environments.

Education, Behavioral Competencies, and Skills

• Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or related fields.
• Experience: 5+ years of experience in data engineering, AI/Gen AI model deployment, and end-to-end architectural design.
• Technical Skills: Proficiency in SQL, Databricks, Python, R, and cloud platforms (e.g., AWS, Azure, GCP). Experience with MLOps tools and frameworks.
• Architectural Skills: Strong understanding of data architecture, data warehousing, and data governance.
• Soft Skills: Excellent communication and leadership skills, with the ability to mentor and guide development teams.

Additional Sections

• AI/Gen AI Focus: Highlight specific experience with AI/Gen AI technologies and frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
• Data Engineering Focus: Emphasize experience with data engineering tools and technologies (e.g., Apache Spark, Kafka, Airflow).
• Production Environment: Detail experience in deploying and managing AI models in production environments, including monitoring and optimization.

WHAT TAKEDA CAN OFFER YOU:

• Takeda is certified as a Top Employer, not only in India, but also globally. No investment we make pays greater dividends than taking good care of our people.
• At Takeda, you take the lead on building and shaping your own career.
• Joining the ICC in Bengaluru will give you access to high-end technology, continuous training and a diverse and inclusive network of colleagues who will support your career growth.

BENEFITS:

It is our priority to provide competitive compensation and a benefit package that bridges your personal life with your professional career. Amongst our benefits are:

• Competitive Salary + Performance Annual Bonus
• Flexible work environment, including hybrid working
• Comprehensive Healthcare Insurance Plans for self, spouse, and children
• Group Term Life Insurance and Group Accident Insurance programs
• Health & Wellness programs including annual health screening, weekly health sessions for employees.
• Employee Assistance Program
• 3 days of leave every year for Voluntary Service in additional to Humanitarian Leaves
• Broad Variety of learning platforms
• Diversity, Equity, and Inclusion Programs
• Reimbursements – Home Internet & Mobile Phone
• Employee Referral Program
• Leaves – Paternity Leave (4 Weeks) , Maternity Leave (up to 26 weeks), Bereavement Leave (5 calendar days)

ABOUT ICC IN TAKEDA:

• Takeda is leading a digital revolution. We're not just transforming our company; we're improving the lives of millions of patients who rely on our medicines every day.
• As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization.

IND - Bengaluru

Employee

Regular

Full time

Company Description

FACE Prep is one of India's largest placement-focused skill development companies, specializing in job preparation for the tech sector. Since its inception in 2008, FACE Prep has helped millions of students kickstart their careers. The company offers a variety of programs, including masterclasses, self-paced courses, and workshops to help students acquire the skills needed for top-paying jobs in tech. FACE Prep's alumni work at leading tech companies like Google, Microsoft, Meta, Adobe, PayPal, and many more.

Role Description

This is a full-time, on-site role for an AI & ML Mentor (Faculty) located in Bengaluru. The AI & ML Mentor will be responsible for delivering quality education through workshops, bootcamps, and mentoring sessions. Day-to-day tasks include preparing instructional materials, guiding students through complex AI and ML concepts, and providing individual mentorship. The role involves staying updated with the latest advancements in AI and ML to ensure the curriculum remains current and effective.

Qualifications

• In-depth knowledge and expertise in Artificial Intelligence (AI) and Machine Learning (ML)
• Experience in developing and delivering instructional content, including workshops and bootcamps
• Proficiency in Python and related libraries such as TensorFlow, PyTorch, and scikit-learn
• Excellent communication and presentation skills
• Ability to mentor and guide students at different stages of learning
• Experience in the education sector or similar role is a plus
• Bachelor's or Master's degree in Computer Science, Data Science, or related field