416 Data Science jobs in New Delhi

B.E with 15+ experience in data Science / AI space.

About the Role

Be a leader in ML & GenAI Space with exposure to Application building.

Responsibilities

• Should have experience in doing Business Development on ML & GenAI space.
• Should have exposure in independently creating demos, PoC’s and accelerators on GenAI space.
• Able to handle entire BD process of its own.
• Can setup a team of smart data scientists and app developers quickly.
• Be an Individual Contributor in the Analytics and Development team and solve real-world problems using cutting-edge capabilities and emerging technologies based on LLM/GenAI/GPT.
• Software development experience in python is needed as backend for UI based applications.
• Create Technical documents e.g., HLD/LLDs/Technical Designs etc., develop, test, and deploy data analytics processes using Python, SQL on Azure/AWS platforms.
• Can interact with client on GenAI related capabilities and use cases.

Qualifications

B.E with 15+ experience in data Science / AI space.

Required Skills

• Experience in ML & GenAI space.
• Business Development experience.
• Software development experience in Python.
• Experience with Azure/AWS platforms.

B.E with 15+ experience in data Science / AI space.
About the Role
Be a leader in ML & GenAI Space with exposure to Application building.

Responsibilities

Should have experience in doing Business Development on ML & GenAI space.
Should have exposure in independently creating demos, PoC’s and accelerators on GenAI space.
Able to handle entire BD process of its own.
Can setup a team of smart data scientists and app developers quickly.
Be an Individual Contributor in the Analytics and Development team and solve real-world problems using cutting-edge capabilities and emerging technologies based on LLM/GenAI/GPT.
Software development experience in python is needed as backend for UI based applications.
Create Technical documents e.g., HLD/LLDs/Technical Designs etc., develop, test, and deploy data analytics processes using Python, SQL on Azure/AWS platforms.
Can interact with client on GenAI related capabilities and use cases.

Qualifications

B.E with 15+ experience in data Science / AI space.

Required Skills
Experience in ML & GenAI space.
Business Development experience.
Software development experience in Python.
Experience with Azure/AWS platforms.

About Tavant:

With 25+ years of experience building innovative digital products and solutions, Tavant provides impactful results to its customers. It has been the frontrunner in driving digital innovation and tech-enabled transformation across a wide range of industries such as Consumer Lending, Manufacturing, Agtech, Media & Entertainment, and Retail in North America, Europe, and Asia-Pacific. Powered by Artificial Intelligence and Machine Learning algorithms, we help our customers improve their operational efficiency, productivity, speed, and accuracy. Our suite of products and solutions are routinely rated high by the industry.

Ours is a challenging workplace where teams are diverse, competitive, and continually searching for tomorrow's technology and brilliant minds to create it. And we don’t focus just on what we do – we also care how we do it. So, bring your talent and ambition to make a difference. We’ll create a world of opportunities for you.

Job Title : Lead Data Science Consultant
Experience : 15-20 years
Work Location : Bangalore/Hyderabad/Noida/Kolkata/Pune
Work mode : Hybrid (3 days WFO)

We are looking for an experienced Senior Lead Data Scientist / ML Engineer with a strong blend of pre-sales expertise, team leadership, and technical proficiency across classical machine learning, deep learning, and generative AI. You will engage in high-level client discussions, drive technical sales strategies, and lead a team to design and implement cutting-edge ML solutions. This is a strategic role requiring both thought leadership and hands-on technical contributions.

Key Responsibilities

Pre-Sales & Client Engagement
Collaborate with the sales and business development teams to identify client needs and formulate AI/ML solutions.
Present technical concepts, project proposals, and proof-of-concepts (POCs) to prospects and clients.
Translate complex client requirements into actionable project scopes, estimates, and technical proposals.
Leadership & Team Management
Provide direction, mentorship, and performance feedback to a team of data scientists and ML engineers.
Establish best practices in solution design, code reviews, model validation, and production deployment.
Drive the strategic roadmap for AI initiatives, ensuring alignment with organizational goals and market trends.
Classical Machine Learning & Statistical Modeling
Apply classical machine learning techniques (e.g., regression, clustering, decision trees, ensemble methods) to solve diverse business problems.
Design and optimize data pipelines, feature engineering processes, and model selection strategies.
Ensure robust model evaluation, tuning, and performance monitoring in production environments.
Deep Learning & Generative AI
Develop and maintain deep learning models using frameworks such as TensorFlow or PyTorch for tasks like computer vision, NLP, or recommendation systems.
Explore and build solutions leveraging generative AI (GANs, VAEs, or transformer-based architectures) for innovative product features and services.
Champion research and experimentation with state-of-the-art AI models, staying ahead of industry advances.
Project Delivery & MLOps
Lead end-to-end ML project lifecycles, from data exploration and model development to deployment and post-launch maintenance.
Implement MLOps best practices (CI/CD, containerization, model versioning) on cloud or on-premise infrastructures.
Collaborate with DevOps and engineering teams to integrate ML solutions seamlessly into existing systems.
Stakeholder Management & Communication
Serve as a key technical advisor to executive leadership, product managers, and client teams.
Communicate complex AI/ML findings in clear, actionable terms to both technical and non-technical audiences.
Advocate data-driven decision-making and foster a culture of innovation within the organization.

Required Qualifications

Education & Experience
Master’s or PhD in Computer Science, Data Science, Engineering, or a related field is preferred.
12+ years of relevant industry experience in data science or ML engineering, with 5+ years in a leadership or management capacity.
Technical Expertise
Pre-Sales: Demonstrated experience in client-facing roles, solutioning, and proposal development.
Classical ML: Skilled in traditional algorithms (regression, classification, clustering, etc.) and statistical methods.
Deep Learning: Hands-on expertise with frameworks (e.g., TensorFlow, PyTorch) for CNNs, RNNs, transformer architectures, etc.
Generative AI: Practical exposure to GANs, VAEs, or large language models, with a track record of building generative models.
MLOps: Familiarity with CI/CD pipelines, Docker/Kubernetes, and cloud platforms (AWS, Azure, GCP).
Leadership & Communication
Proven ability to mentor and lead data science/ML engineering teams to meet project goals.
Exceptional communication skills for presenting to clients, stakeholders, and executive leadership.
Experience in agile methodologies and project management, balancing multiple projects simultaneously.
Preferred / Bonus Skills
Experience in big data ecosystems (Spark, Hadoop) for large-scale data processing.
Background in NLP, computer vision, or recommendation systems.
Knowledge of DevOps tools (Jenkins, GitLab CI, Terraform) for infrastructure automation.
Track record of published research or contributions to open-source AI projects.

About the Company

ZeTheta Algorithms Private Limited is a FinTech start-up which has been recently set up and is developing innovative AI tools.

the Role

As a Data Scientist intern, you will work on cutting-edge projects involving financial data analysis, investment research, and risk modelling. You will have the opportunity to engage in multiple mini-projects or take up a focused innovation-based research project. The project experience is designed to provide practical exposure to data science in the context of asset management, trading, and financial technology. We provide problem statements, methodology and after you submit your solution to develop the solutions/ model, we also showcase to you sample solution. You can use our sample solution to modify your project submission and expand further based on suggestions given in our sample solution. You can opt for your own research based data science solution to develop/ model.

Responsibilities

- Conduct data cleaning, wrangling, and pre-processing for financial datasets.
- Assist investment teams in equity research, fixed income research, portfolio management, and economic analysis.
- Apply statistical techniques to financial problems such as credit risk modelling, probability of default, and value-at-risk estimation.
- Work with big data sources including financial reports, macroeconomic datasets, and alternative investment data.
- Use either one – Python, Excel or R to analyse, visualize, and model financial data.
- Participate in research projects related to quantitative trading, financial derivatives, and portfolio optimization.

Who Should Apply?

- Any student even without coding skills can upskill (self learning) to develop Data Science Solutions. Some basic knowledge of Excel or Python or R script can help complete the projects quicker. We permit the use of all LLMs/ NLPs to help students to develop the solutions.
- Strong problem-solving and analytical skills.
- Able to self-learn and work independently in a remote, flexible environment.

Internship Details

- Duration: Option of 1 month, 2 month, 3 month, 4 month or 6 months
- Timing: Self-paced.
- Type: Unpaid

NLP Data Science Intern

Did you notice a shortage of food at supermarkets during covid? Have you heard about the recent issues in the global shipping industry? or perhaps you’ve heard about the shortages of microchips? These problems are called supply chain disruptions. They have been increasing in frequency and severity. Supply chain disruptions are threatening our very way of life.

Our vision is to advance society’s capacity to withstand shocks and stresses. Kavida.ai believes the only way to ensure security is through supply chain resiliency. We are on a mission to help companies proactively manage disruption supply chain disruption risks using integrated data.

Our Story

In March 2020 over 35 academics, data scientists, students, and software engineering volunteers came together to address the food shortage issues caused by the pandemic - Covid19foodsupply.com. A core team of 9 was formed and spun off into a startup and the rest is history.

Our investors include one of the world's largest supply chain quality & compliance monitoring companies, a £1.25bn apparel manufacturer, and some very impressive angel investors.

Social Impact:

Social impact is in our DNA. We believe private sector innovation is the only way to address social problems at scale. If we achieve our mission, humanity will always have access to its essential goods for sustenance. No more shortages of food, PPE, medicine, etc.

Our Culture:

Idea Meritocracy:

The best ideas win. We only care about what is right, not who is right. We know arriving at the best answer requires constructive tension. Sometimes it can get heated but it's never personal. Everyone contributes to better ideas knowing they will be heard but also challenged.

Drivers Not Passengers:

We think as owners who drive the bus, not as passengers. We are self-starters and never wait for instructions. We are hungry for autonomy, trust, and responsibility. Everyone is a leader because we know leadership is a trait, not a title. Leaders drive growth and navigate the chaos.

We Figure Out The Answers:

We trust our ability to figure stuff out. We do not need all the information to start answering the question. We can connect the dots and answer difficult questions with logic.

Customer & Mission Obsessed:

Our customers are our heroes and we are obsessed with helping them. We are obsessed with; understanding their supply chains better, resolving their biggest headaches, and advancing their competitiveness.

Learning and growth

We all take personal responsibility for becoming smarter, wiser, more skilled, happier. We are obsessed with learning about our industry and improving our own skills. We are obsessed with our personal growth; to become more.

Job Description:

As a member of our Research team, you will be responsible for researching, developing, and coding Agents using state-of-the-art LLM's with automated pipelines.

- Write code for the development of our ML engines and micro-services pipelines.
- use, optimize, train, and evaluate state-of-the-art GPT models.
- research and Develop Agentic pipelines using LLM's.
- research and develop RAG based pipeline using vector DB's .

Essential Requirements:

- prompt engineering and Agentic LLm frameworks like langchain/llama index
- good enough undersanding of vectors/tensors and RAG pipelines
- Knowledge of building NLP systems using transfer learning or building custom NLP systems from scratch using TensorFlow or PyTorch.
- In-depth knowledge of DSA, async, python, and containers.
- Knowledge of transformers and NLP techniques is essential, and deployment experience is a significant advantage.

Salary Range: ₹15000 - ₹25000

We are offering a full-time internship position to final-year students. The internship will last for an initial period of 6-12 months before converting to a full-time job, depending on suitability for both parties. If the applicant is a student who needs to return to university, they can continue with the program on a part-time basis.

Are you passionate about transforming data into actionable insights? Do you thrive in a fast-paced, innovative environment? We’re looking for a Data Science Analyst to join our team and help us drive data-informed decisions that shape the future of our business.

What You’ll Do

- Analyze complex datasets to uncover trends, patterns, and actionable insights.
- Develop predictive models and statistical analyses to support business strategies.
- Collaborate with cross-functional teams to understand data needs and deliver solutions.
- Build dashboards and visualizations to communicate findings effectively to stakeholders.
- Stay ahead of data trends and implement best practices in analytics and machine learning.

What We’re Looking For

- Bachelor's or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
- Strong programming skills in Python, R, or SQL.
- Experience with data visualization tools (Tableau, Power BI, etc.).
- Solid understanding of machine learning algorithms and statistical methods.
- Excellent problem-solving and communication skills.
- A curious mindset with a passion for exploring data.

Why Join Us?

- Opportunity to work on exciting, high-impact projects.
- Collaborative and supportive work environment.
- Resources for professional development and growth.
- A chance to shape the future of data-driven decision-making.

About Tavant:

With 25+ years of experience building innovative digital products and solutions, Tavant provides impactful results to its customers. It has been the frontrunner in driving digital innovation and tech-enabled transformation across a wide range of industries such as Consumer Lending, Manufacturing, Agtech, Media & Entertainment, and Retail in North America, Europe, and Asia-Pacific. Powered by Artificial Intelligence and Machine Learning algorithms, we help our customers improve their operational efficiency, productivity, speed, and accuracy. Our suite of products and solutions are routinely rated high by the industry.

Ours is a challenging workplace where teams are diverse, competitive, and continually searching for tomorrow's technology and brilliant minds to create it. And we don’t focus just on what we do – we also care how we do it. So, bring your talent and ambition to make a difference. We’ll create a world of opportunities for you.

Job Title : Lead Data Science Consultant

Experience : 15-20 years

Work Location : Bangalore/Hyderabad/Noida/Kolkata/Pune

Work mode : Hybrid (3 days WFO)

We are looking for an experienced Senior Lead Data Scientist / ML Engineer with a strong blend of pre-sales expertise, team leadership, and technical proficiency across classical machine learning, deep learning, and generative AI. You will engage in high-level client discussions, drive technical sales strategies, and lead a team to design and implement cutting-edge ML solutions. This is a strategic role requiring both thought leadership and hands-on technical contributions.

Key Responsibilities

Pre-Sales & Client Engagement

• Collaborate with the sales and business development teams to identify client needs and formulate AI/ML solutions.
• Present technical concepts, project proposals, and proof-of-concepts (POCs) to prospects and clients.
• Translate complex client requirements into actionable project scopes, estimates, and technical proposals.

Leadership & Team Management

• Provide direction, mentorship, and performance feedback to a team of data scientists and ML engineers.
• Establish best practices in solution design, code reviews, model validation, and production deployment.
• Drive the strategic roadmap for AI initiatives, ensuring alignment with organizational goals and market trends.

Classical Machine Learning & Statistical Modeling

• Apply classical machine learning techniques (e.g., regression, clustering, decision trees, ensemble methods) to solve diverse business problems.
• Design and optimize data pipelines, feature engineering processes, and model selection strategies.
• Ensure robust model evaluation, tuning, and performance monitoring in production environments.

Deep Learning & Generative AI

• Develop and maintain deep learning models using frameworks such as TensorFlow or PyTorch for tasks like computer vision, NLP, or recommendation systems.
• Explore and build solutions leveraging generative AI (GANs, VAEs, or transformer-based architectures) for innovative product features and services.
• Champion research and experimentation with state-of-the-art AI models, staying ahead of industry advances.

Project Delivery & MLOps

• Lead end-to-end ML project lifecycles, from data exploration and model development to deployment and post-launch maintenance.
• Implement MLOps best practices (CI/CD, containerization, model versioning) on cloud or on-premise infrastructures.
• Collaborate with DevOps and engineering teams to integrate ML solutions seamlessly into existing systems.

Stakeholder Management & Communication

• Serve as a key technical advisor to executive leadership, product managers, and client teams.
• Communicate complex AI/ML findings in clear, actionable terms to both technical and non-technical audiences.
• Advocate data-driven decision-making and foster a culture of innovation within the organization.

Required Qualifications

Education & Experience

• Master’s or PhD in Computer Science, Data Science, Engineering, or a related field is preferred.
• 12+ years of relevant industry experience in data science or ML engineering, with 5+ years in a leadership or management capacity.

Technical Expertise

• Pre-Sales: Demonstrated experience in client-facing roles, solutioning, and proposal development.
• Classical ML: Skilled in traditional algorithms (regression, classification, clustering, etc.) and statistical methods.
• Deep Learning: Hands-on expertise with frameworks (e.g., TensorFlow, PyTorch) for CNNs, RNNs, transformer architectures, etc.
• Generative AI: Practical exposure to GANs, VAEs, or large language models, with a track record of building generative models.
• MLOps: Familiarity with CI/CD pipelines, Docker/Kubernetes, and cloud platforms (AWS, Azure, GCP).

Leadership & Communication

• Proven ability to mentor and lead data science/ML engineering teams to meet project goals.
• Exceptional communication skills for presenting to clients, stakeholders, and executive leadership.
• Experience in agile methodologies and project management, balancing multiple projects simultaneously.

Preferred / Bonus Skills

• Experience in big data ecosystems (Spark, Hadoop) for large-scale data processing.
• Background in NLP, computer vision, or recommendation systems.
• Knowledge of DevOps tools (Jenkins, GitLab CI, Terraform) for infrastructure automation.
• Track record of published research or contributions to open-source AI projects.

B.E with 15+ experience in data Science / AI space.

About the Role

Be a leader in ML & GenAI Space with exposure to Application building.

Responsibilities

• Should have experience in doing Business Development on ML & GenAI space.
• Should have exposure in independently creating demos, PoC’s and accelerators on GenAI space.
• Able to handle entire BD process of its own.
• Can setup a team of smart data scientists and app developers quickly.
• Be an Individual Contributor in the Analytics and Development team and solve real-world problems using cutting-edge capabilities and emerging technologies based on LLM/GenAI/GPT.
• Software development experience in python is needed as backend for UI based applications.
• Create Technical documents e.g., HLD/LLDs/Technical Designs etc., develop, test, and deploy data analytics processes using Python, SQL on Azure/AWS platforms.
• Can interact with client on GenAI related capabilities and use cases.

Qualifications

B.E with 15+ experience in data Science / AI space.

Required Skills

• Experience in ML & GenAI space.
• Business Development experience.
• Software development experience in Python.
• Experience with Azure/AWS platforms.