595 Data Scientist jobs in New Delhi

• Develop and deploy advanced predictive models using machine learning and statistical techniques.
• Analyze large, complex datasets to identify patterns and trends.
• Translate business problems into data science solutions.
• Design and execute experiments to test hypotheses and validate models.
• Interpret model results and communicate insights to stakeholders.
• Clean, transform, and prepare data for analysis.
• Stay up-to-date with the latest advancements in data science and AI.
• Collaborate with engineering and product teams to integrate models into production systems.
• Mentor junior data scientists and contribute to team knowledge sharing.
• Ensure data quality and integrity throughout the analytical process.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 7 years of experience in data science, with a focus on predictive modeling.
• Proven expertise in machine learning algorithms (e.g., regression, classification, clustering, time series).
• Proficiency in programming languages such as Python or R.
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
• Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
• Strong understanding of statistical concepts and experimental design.
• Excellent communication, presentation, and storytelling skills.
• Ability to work independently in a remote setting and manage projects effectively.

• Design, develop, and implement advanced predictive models and machine learning algorithms to solve complex business problems across various domains, such as customer behavior, risk assessment, and operational efficiency.
• Perform extensive data exploration, feature engineering, and data mining to identify patterns, trends, and insights within large and complex datasets.
• Evaluate and validate model performance using appropriate statistical methods and metrics, iterating to improve accuracy and robustness.
• Collaborate closely with business stakeholders, product managers, and engineering teams to understand requirements, define analytical approaches, and deploy models into production environments.
• Communicate complex analytical findings and recommendations clearly and concisely to both technical and non-technical audiences through compelling visualizations and presentations.
• Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence, exploring and adopting new techniques and tools.
• Mentor junior data scientists, providing technical guidance and fostering a culture of continuous learning and innovation.
• Develop and maintain high-quality, well-documented code for data analysis, model development, and deployment pipelines.
• Contribute to the strategic direction of the data science function by identifying new opportunities for data-driven solutions.
• Ensure data integrity, privacy, and security in all analytical processes.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field.
• Minimum of 6 years of experience in data science, with a strong focus on building and deploying predictive models and machine learning systems.
• Proficiency in programming languages commonly used in data science, such as Python (with libraries like scikit-learn, TensorFlow, PyTorch, Pandas, NumPy) or R.
• Extensive experience with SQL and working knowledge of big data technologies (e.g., Spark, Hadoop).
• Demonstrated expertise in statistical modeling, time series analysis, classification, regression, clustering, and other machine learning techniques.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps principles is a significant advantage.
• Strong understanding of data mining, data warehousing, and data visualization techniques.
• Excellent problem-solving, analytical, and critical thinking skills.
• Outstanding communication and presentation skills, with the ability to explain technical concepts to diverse audiences.
• Proven ability to work independently and collaboratively in a remote team environment.

About the Company

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.

About the Role

A Developer, you will design, develop, train, and implement machine learning and deep learning models capable of processing large datasets and generating actionable insights.

Responsibilities

• Strong Programming skills in Python or Scala.
• Hands-on experience in vector databases like Pinecone, and Chroma db.
• Deep knowledge of AI technologies like machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn (e.g., APIs, microservices, event-driven IT, MLflow).
• Extensive experience writing production-ready code, hands-on experience with different programming paradigms and (MLOps and DevSecOps).
• Practical and professional experience contributing to and maintaining a large code base with code versioning systems such as Git.
• Minimum 8-10 years of experience in implementing automation initiatives based on Gen AI / ML, NLP, CPA, CoPilot, Gemini, RPA and other tools.
• Hands-on experience on programming (Python, Scala) and working with Gen-AI frameworks, LLM Models.
• Hands-on Experience to all SDLC Phases.
• Deploy AI models into production environments, ensuring they integrate smoothly with existing software systems.
• Monitor, update & refine the performance of deployed models.
• Should be skilled in problem-solving, Data analysis and Interpretation, pattern recognition, Algorithmic thinking, critical thinking, debugging and troubleshooting.
• Automate model packaging and deployment into production environments, with traceability on model version, experimentation and control checks.
• Building automated model performance monitoring services to monitor model health and report data to data scientists, model owner, and model validators.
• Builds and mentors architecture teams.
• Have the mindset to build Enterprise-grade solutions aligned to the industry's best practices.
• Build reusable frameworks and platforms to allow data scientists, devops teams to train and deploy models.
• Exceptional written, verbal, and interpersonal communication skills to articulate strategies to technical audiences.
• Collaborate to create propositions on AI / GenAI for clients.
• Willingness to quickly learn and start using various technologies and contribute to the COE.

Qualifications

• Mandatory Skills: PYTHON

Required Skills

• Strong Programming skills in Python or Scala.
• Hands-on experience in vector databases like Pinecone, and Chroma db.
• Deep knowledge of AI technologies like machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.

Preferred Skills

• Experience with MLOps and DevSecOps.
• Hands-on experience with Gen AI / ML, NLP, CPA, CoPilot, Gemini, RPA.

Data Scientist

We are seeking a Data Scientist with around 3 years of experience to join our analytics and machine learning team in the Ad Tech domain. In this role, you will apply statistical and machine learning techniques to improve campaign targeting, audience segmentation, and recommendation systems. You will collaborate with engineers, analysts, and product teams to transform data into insights and deploy models that directly impact business outcomes. This position is ideal for someone eager to take ownership of end-to-end projects while continuing to expand their expertise in advanced machine learning and applied statistics.

Key Responsibilities

• Develop and deploy machine learning and statistical models to solve business problems in advertising and marketing.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, and actionable insights.
• Design and run experiments (e.g., A/B testing) to evaluate impact and validate hypotheses.
• Work with engineers to build and maintain scalable data pipelines that support modeling and analytics.
• Communicate results effectively through dashboards, visualizations, and presentations .
• Stay up to date with new techniques in machine learning, causal inference, and recommendation systems and apply them where relevant.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Physics).
• ~3 years of experience applying machine learning and statistical methods in a professional setting.
• Strong proficiency in Python or R and SQL .
• Experience with ML frameworks such as scikit-learn, TensorFlow, or PyTorch .
• Hands-on knowledge in at least one of the following: A/B testing, causal inference, NLP, or recommendation systems .
• Strong problem-solving, analytical, and communication skills.

Nice-to-Have

• Prior experience in Ad Tech, digital marketing, or related industries .
• Familiarity with big data and distributed systems (e.g., Spark, Databricks, GCP).
• Experience with time series forecasting or advanced NLP techniques .

Role: Data Scientist, Delhi (Gurugram), India - Salary Band P2

Fiddlehead Technology is a Canadian leader in advanced analytics and AI-driven solutions, helping global companies unlock value from their data. We specialize in applying machine learning, predictive forecasting, and Generative AI to solve complex business problems and empower smarter decision-making.

Our culture thrives on innovation, collaboration, and continuous learning. We invest in our people by offering structured opportunities for professional development, a healthy work-life balance, and exposure to cutting-edge AI/ML projects across industries. At Fiddlehead, employees are encouraged to explore, create, and grow while contributing to high-impact solutions.

Fiddlehead Technology is a data science company with over 10 years of experience helping

consumer-packaged goods (CPG) companies harness the power of machine learning and

AI. We transform data into actionable insights, building predictive models that drive

efficiency, growth, and competitive advantage. With increasing demand for our solutions,

we’re expanding our global team.

We are seeking Data Scientists to collaborate with our team based in Canada in developing

advanced forecasting models and optimization algorithms for leading CPG manufacturers

and service providers. In this role, you’ll monitor model performance in production,

addressing challenges like data drift and concept drift, while delivering data-driven insights

that shape business decisions.

What You’ll Bring

• Education and/or professional experience in data science and forecasting

• Proficiency with forecasting tools and libraries, ideally in Python

• Knowledge of machine learning and statistical concepts

• Strong analytical and problem-solving abilities

• Ability to communicate complex findings to non-technical stakeholders

• High attention to detail and data accuracy

• Degree in Statistics, Data Science, Computer Science, Engineering, or related field

(Bachelor’s, Master’s, or PhD)

At Fiddlehead, you’ll work on meaningful projects that advance predictive forecasting and

sustainability in the CPG industry. We offer a collaborative, inclusive, and supportive

environment that prioritizes professional development, work-life balance, and continuous

learning. Our team members enjoy dedicated time to expand their skills while contributing

to innovative solutions with real-world impact.

We carefully review every application and are committed to providing a response. Candidates selected will be invited to an in-person or virtual interview. To ensure equal access, we provide accommodations during the recruitment process for applicants with disabilities. If you require accommodations, please reach out to our team through the contact page on our website. At Fiddlehead, we are dedicated to fostering an inclusive and accessible environment where every employee and customer is respected, valued, and supported. We welcome applications from women, Indigenous peoples, persons with disabilities, ethnic and visible minorities, members of the LGBT+ community, and others who can help enrich the diversity of our workforce.

We offer a competitive compensation package with performance-based incentives and opportunities to contribute to impactful projects. Employees benefit from mentorship, training, and active participation in AI communities, all within a collaborative culture that values innovation, creativity, and professional growth.

Job title – Applied Scientist / Data Scientist

Who are we?

We are an Artificial Intelligence company bringing the speed and insight of Applied AI to

visual assessment. Trained on millions of data points, our AI-powered solutions connect

everyone involved in insurance, repairs, and sales of homes and cars – helping people work

faster and smarter, while reducing friction and waste.

Founded in 2014, We are now the AI tool of choice for world-leading insurance and

automotive companies. Our solutions unlock the potential of Applied AI to transform the

whole recovery ecosystem, from assessing damage and accelerating claims and repairs to

recycling parts. They help make response to recovery up to ten times faster – even after

full-scale disasters like floods and hurricanes.

it has a world-class culture, backed up by our team, making us a global employer of

choice!

We're a diverse team, uniting individuals of over 40 different nationalities and from varied

backgrounds, with machine learning researchers and motor engineers collaborating together

on a daily basis. We empower each team member to have tangible impact and grow their

own scope by intentionally building a culture centred around collaboration, transparency,

autonomy and continuous learning.

Our team shapes the technical foundations used across all products, currently

focused on auto insurance and natural disaster recovery. Our mission is to leverage the

latest ML research to solve hard science problems necessary to transform the insurance

industry (& more). We focus on creating mission-critical AI systems solving some of the

trickiest problems in computer vision, and our innovation has already improved the lives of

100,000s of people so far (really). We’re a fun and ambitious team, and looking for someone

to join us on our exciting journey!

Auto organization – Who we are & What we do

Our organization is responsible for building products for the automotive industry. We have

already built 2 products (Estimating, Review) sold globally to insurers.

Our long-term vision is to build a platform ecosystem that we can leverage to effortlessly

build new products and use cases. Our current mission is to create a reliable and safe

“virtual” motor appraiser/expert as a service, we can leverage to solve many use cases

across the automotive industry. We are doing so, by building high-quality input capture

mechanisms for our users, creating a state-of-the-art damage assessment stack for auto

damage, or delivering explainable and human-centric decision-making engines.

We are working hand-in-hand with engineering teams to turn our R&D prototypes into

mission-critical systems.

What will you be doing?

As an Applied scientist, you will contribute to the design, development, and improvement of

AI/ML models and systems. You will be expected to:

- Work with applied scientists, data scientist, software engineers and product partners to

design and deliver AI/ML solutions in production at scale.

- Design and develop AI/ML models, workflows and end-to-end pipelines for data

preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and

design of our ML models and systems.

- Deliver customer-facing and/or underlying AI/ML solutions that empower our platform to

provide the best experience for our customers.

What we’re looking for.

BASIC QUALIFICATIONS

- Master's in Computer Science, Machine Learning, or related quantitative field. A PhD in

Computer Science or related fields with a focus on Machine Learning is a strong plus.

- Extensive knowledge and practical experience in several of the following areas: machine

vision (classical methods and deep learning) and information retrieval. Natural language

processing is a plus.

- Demonstrated experience in building scalable AI/ML models and systems and delivering

end-to-end solutions in a production environment.

- Experience programming in Python, C++, or related languages

PREFERRED QUALIFICATIONS

- Publications at top-tier peer-reviewed conferences or journals or a proven track record of

industry innovation in creating novel solutions and advancing the state of the art.

- Experience with machine learning libraries and deep learning frameworks (TensorFlow,

PyTorch, etc.)

- Experience with end-to-end software development and life cycle of machine learning

solutions.

- Excellent verbal and written communication skills, with the ability to communicate complex

technical concepts and solutions to all levels of the organization

Role Overview: Data Scientist

Location: Remote/ Indore/ Mumbai/ Chennai/ Gurugram

Experience: Min 5 Years

Work Mode: Remote

Notice Period: Max. 30 Days (45 for Notice Serving)

Interview Process: 2 Rounds

Interview Mode: Virtual Face-to-Face

Interview Timeline: 1 Week

Industry: Must be from a BPO/ KPO/ Shared Services or Healthcare Org.

Key Responsibilities:

• AI/ML Development & Research
• Design, develop, and deploy advanced machine learning and deep learning models to solve complex business problems.
• Implement and optimize Large Language Models (LLMs) and Generative AI solutions for real-world applications.
• Build agent-based AI systems with autonomous decision-making capabilities.
• Conduct cutting-edge research on emerging AI technologies and explore their practical applications.
• Perform model evaluation, validation, and continuous optimization to ensure high performance.

• Cloud Infrastructure & Full-Stack Development:
• Architect and implement scalable, cloud-native ML/AI solutions using AWS, Azure, or GCP.
• Develop full-stack applications that seamlessly integrate AI models with modern web technologies.
• Build and maintain robust ML pipelines using cloud services (e.g., SageMaker, ML Engine).
• Implement CI/CD pipelines to streamline ML model deployment and monitoring processes.
• Design and optimize cloud infrastructure to support high-performance computing workloads.

• Data Engineering & Database Management
• Design and implement data pipelines to enable large-scale data processing and real-time analytics.
• Work with both SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) to manage structured and unstructured data.
• Optimize database performance to support machine learning workloads and real-time applications.
• Implement robust data governance frameworks and ensure data quality assurance practices.
• Manage and process streaming data to enable real-time decision-making.

• Leadership & Collaboration
• Mentor junior data scientists and assist in technical decision-making to drive innovation.
• Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to develop solutions that align with organizational goals.
• Present findings and insights to both technical and non-technical audiences in a clear and actionable manner.
• Lead proof-of-concept projects and innovation initiatives to push the boundaries of AI/ML applications.

Required Qualifications:

• Education & Experience
• Master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 5+ years of hands-on experience in data science and machine learning, with a focus on real-world applications.
• 3+ years of experience working with deep learning frameworks and neural networks.
• 2+ years of experience with cloud platforms and full-stack development.

• Technical Skills - Core AI/ML
• Machine Learning: Proficient in Scikit-learn, XGBoost, LightGBM, and advanced ML algorithms.
• Deep Learning: Expertise in TensorFlow, PyTorch, Keras, CNNs, RNNs, LSTMs, and Transformers.
• Large Language Models: Experience with GPT, BERT, T5, fine-tuning, and prompt engineering.
• Generative AI: Hands-on experience with Stable Diffusion, DALL-E, text-to-image, and text generation models.
• Agentic AI: Knowledge of multi-agent systems, reinforcement learning, and autonomous agents.

• Technical Skills - Development & Infrastructure
• Programming: Expertise in Python, with proficiency in R, Java/Scala, JavaScript/TypeScript.
• Cloud Platforms: Proficient with AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI.
• Databases: Proficiency with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB).
• Full-Stack Development: Experience with React/Vue.js, Node.js, FastAPI, Flask, Docker, Kubernetes.
• MLOps: Experience with MLflow, Kubeflow, model versioning, and A/B testing frameworks.
• Big Data: Expertise in Spark, Hadoop, Kafka, and streaming data processing.

Non Negotiables:

• Cloud Infrastructure - ML/AI solutions on AWS, Azure, or GCP
• Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.)
• Implement CI/CD pipelines for ML model deployment and monitoring
• Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.)
• Machine Learning: Scikit-learn
• Deep Learning: TensorFlow
• Programming: Python (expert), R, Java/Scala, JavaScript/TypeScript
• Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda)
• Vector databases and embeddings (Pinecone, Weaviate, Chroma)
• Knowledge of LangChain, LlamaIndex, or similar LLM frameworks.
• Industry: Must be a BPO or Healthcare Org.