3,827 Data Science Manager jobs in India

Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline) • Good programming skills in Python with strong working knowledge of Python’s numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc. • Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) • Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning • Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models • Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. • Predictive modelling experience in Python (Time Series/ Multivariable/ Causal) • Experience applying various machine learning techniques and understanding the key parameters that affect their performance • Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs • Excellent verbal and written communication • Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects.

Job Description:

• Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline)

• Good programming skills in Python with strong working knowledge of Python’s numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc.

• Experience with SQL, Excel, Tableau/ Power BI, PowerPoint

• Predictive modelling experience in Python (Time Series/ Multivariable/ Causal)

• Experience applying various machine learning techniques and understanding the key parameters that affect their performance

• Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs

• Excellent verbal and written communication

• Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects.

Roles & Responsibilities:

• Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities:

• Connect with internal / external POC to understand the business requirements

• Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis

• Create project plan and sprints for milestones / deliverables

• Spin VM, create and optimize clusters for Data Science workflows

• Create data pipelines to ingest data effectively

• Assure the quality of data with proactive checks and resolve the gaps

• Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms

• Research whether similar solutions have been already developed before building ML models

• Create optimized data models to query relevant data efficiently

• Run relevant ML / DL algorithms for business goal seek

• Optimize and validate these ML / DL models to scale

• Create light applications, simulators, and scenario builders to help business consume the end outputs

• Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively

• Integrate and operationalize the models in client ecosystem

• Document project artifacts and log failures and exceptions.

• Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedbacks

Role: Data Science Manager

Experience: 5+ years (with at least 2 years managing a technical team)

Location: Bengaluru/ Remote within India

Compensation: 38-40 LPA Based on experience

Role Overview:

We are seeking an experienced Data Science Manager to lead and grow our data science function, driving cutting-edge machine learning initiatives that power Rocket Learning’s education platform. The ideal candidate will bring strong hands-on experience in deep learning and MLOps, along with demonstrated leadership in managing technical teams. This role will be instrumental in scaling our generative AI and predictive modeling capabilities, supporting impactful interventions across our programs and communities.

Key Areas of Responsibility

Team Leadership and Management

• Lead and mentor a team of data scientists, fostering a culture of collaboration, innovation, and accountability.
• Provide day-to-day technical guidance, career development, and performance feedback to team members.
• Take full ownership of the mentorship and management of the data science team.

Machine Learning and AI Innovation

• Design and implement scalable ML/DL models to support program delivery and engagement.
• Build and manage infrastructure to serve predictions at scale , ensuring reliability and performance.
• Drive adoption of generative modeling and large language model (LLM) use cases relevant to education.

MLOps and Deployment

• Collaborate with engineering and product teams to deploy ML models using FastAPI, Docker, Kubernetes .
• Own and improve CI/CD pipelines for model development and deployment.
• Ensure model performance monitoring and retraining workflows are in place

Strategic Collaboration

• Work with analytics, product, and engineering to identify high-leverage ML opportunities.
• Stay ahead of emerging AI trends and translate them into actionable innovations for the organization.

Responsibilities in Detail

• Develop and refine machine learning models for real-time and batch prediction.
• Implement deep learning solutions using frameworks like PyTorch or TensorFlow .
• Fine-tune and evaluate large language models for use in community engagement, content generation, and personalization.
• Optimize model deployment pipelines to ensure low latency and high throughput.
• Integrate ML solutions into our product and data infrastructure.
• Maintain strong documentation, reproducibility, and experiment tracking.
• Champion ethical and inclusive AI practices in educational applications

Critical Success Factors

Technical Expertise:

• Strong understanding of machine learning, deep learning, and generative AI concepts .
• Proven experience with PyTorch or TensorFlow for model development.
• Hands-on experience with FastAPI , Docker , and Kubernetes for model deployment.
• Familiarity with MLOps , CI/CD, and infrastructure for scaling AI systems.
• Experience with LLM fine-tuning and model serving at scale.
• Strategic Thinking:
• Ability to translate organizational needs into practical AI solutions.
• Strong judgment around trade-offs between accuracy, interpretability, and scalability.
• Collaboration Skills:
• Excellent communication skills to work with technical and non-technical stakeholders.
• Comfort working in a fast-paced, mission-driven, and agile environment.

Role Overview

As a Manager-Delivery , you will be at the forefront of managing end-to-end project execution. You will collaborate with Engagement Managers, Account Delivery Managers, and client stakeholders to design, develop, and implement data-driven solutions. Your leadership will be pivotal in ensuring high-quality project delivery, building strong client relationships, and guiding a high-performance team.

Key Responsibilities

• Project Leadership & Execution :
• Collaborate with internal and client teams to define business requirements and create comprehensive project plans aligned with project scope and objectives.
• Design effective solutions that enable clients to achieve their goals and optimize their operations.
• Allocate tasks to team members based on their skills and expertise, ensuring efficient resource utilization.
• Lead project execution, track milestones, monitor progress, and ensure the project stays within scope, timeline, and budget.
• Oversee and ensure the quality of deliverables across all project phases, including reports, codes, presentations, and documentation.
• Team Leadership & Development :
• Provide both technical and business guidance to team members, fostering a culture of learning and growth.
• Lead scrum meetings, daily stand-ups, and Weekly Business Reviews (WBR) with clients to ensure alignment on progress and deliverables.
• Build an environment of mutual trust and respect, encouraging experimentation and the adoption of innovative delivery approaches.
• Mentor team members to build a high-performance workplace, focusing on skills development and career growth.
• Quality & Compliance :
• Ensure compliance with best practices and established processes for quality assurance, including the use of checklists, coding standards, and peer reviews.
• Develop action plans to improve delivery scores and ensure client satisfaction with project execution.
• Client Engagement & Communication :
• Work closely with mid-management-level clients, providing clarity on the project’s progress, outcomes, and business impact.
• Craft and deliver compelling presentations to communicate complex data insights in an understandable way.
• Balance pragmatic alternatives with ideal solutions, ensuring that business priorities, deadlines, and budgets are managed effectively.

Required Skills

Technical Skills :

• Advanced knowledge of probability and statistics.
• Expertise in Practical Machine Learning , including awareness of key pitfalls and solutions.
• Intermediate proficiency in SQL and Python.
• Intermediate knowledge of project management methodologies and tools.
• Proficiency in MS Office applications : Excel, PowerPoint, and Word.

Non-Technical Skills :

• Strong business acumen with the ability to evaluate the financial impact of decisions.
• Ability to storyboard presentations effectively and hold productive conversations with mid-management-level clients.
• Leadership : Proven ability to lead teams, balance priorities, and make data-driven decisions.
• People Skills : Strong capabilities in conflict resolution, empathy, communication, listening, and negotiation.
• Self-driven with a strong sense of ownership and accountability.

Good to Have Skills

Technical Skills :

• Advanced knowledge of project management methodologies and tools.
• Advanced proficiency in SQL and Python.
• Knowledge of advanced data science areas like time series forecasting , Bayesian data analysis , Operations Research , and domain-specific analytics such as Pricing Analytics , Media Mix Modeling , and B2B/B2C Customer Analytics .

Non-Technical Skills :

• Experience in solution proposals , collaborating with growth, customer success, and central solutioning functions to drive business opportunities.

Job Overview

We are seeking an experienced leader to join our team as a Data Science Manager. In this role, you will be responsible for developing and implementing advanced analytics solutions that drive business growth and customer satisfaction.

Key Responsibilities

• Leverage data analytics to inform business decisions and drive strategic initiatives
• Collaborate with cross-functional teams to support solutioning for proposals, planning, and execution of programs
• Establish credibility by thought partnering with pre-sales and customer teams on analytics topics
• Communicate analytical insights through sophisticated synthesis and packaging of results
• Support build collateral of documents to enhance core capabilities and supporting reference for internal documents
• Contributes to team's content & IP development; Mentor team on analytical methodologies and platforms and help in quality checks
• Develop and implement analytics strategies, frameworks, and best practices to ensure accurate data collection, analysis, and reporting
• Define and document data governance policies and procedures to ensure data quality, security, and compliance with regulations

Requirements

You must have:

• A minimum of 15 years of experience in analytics, machine learning, business intelligence, and data modeling
• A strong understanding of data analytics tools and technologies, including hands-on experience in applying appropriate analytics techniques to build statistical models
• Working knowledge of Python and SQL, as well as proficiency in at least one data visualization tool such as Power BI or Tableau
• Experience across structured and unstructured data (text) leveraging classification, regression, unsupervised, NLP, and other techniques
• Excellent problem-solving and analytical skills, with the ability to think strategically and provide data-driven insights

Benefits

This is an exciting opportunity to join a dynamic team and contribute to driving business success. If you are passionate about data science and analytics, we encourage you to apply for this role.