Data Science Delivery Lead

About the Job

We are seeking an experienced Data Science Delivery Lead to drive the successful delivery of large-scale AI, Machine Learning, Advanced Analytics, and Data Science programs. In this role, you will be responsible for identifying and solving complex business challenges, shaping data science and AI roadmaps, and ensuring the successful execution of end-to-end analytics initiatives.

You will provide strategic leadership across data science teams while partnering closely with business stakeholders, engineering teams, clients, and leadership to deliver measurable business outcomes through data-driven solutions.

Key Responsibilities

1. Lead the identification and definition of complex business problems and translate them into scalable analytics, AI, and machine learning solutions that create measurable business value.
2. Develop and maintain data science and AI roadmaps aligned with client and organizational priorities, adapting them based on changing business needs, emerging technologies, and stakeholder feedback.
3. Drive end-to-end delivery of analytics programs, ensuring successful execution from problem framing and data acquisition to model deployment, monitoring, and business adoption.
4. Partner with clients and business stakeholders to understand strategic objectives, define success metrics, and establish data-driven approaches to solving critical business challenges.
5. Oversee the execution of multiple data science engagements, ensuring quality, timeliness, scalability, and adherence to best practices.
6. Manage cross-functional teams comprising Data Scientists, ML Engineers, Data Engineers, Product Managers, and Domain Consultants to achieve program goals.
7. Establish governance frameworks, operational excellence processes, and delivery standards to improve productivity, predictability, and business impact.
8. Communicate complex analytical concepts, insights, and recommendations to both technical and non-technical stakeholders in a transparent and compelling manner.
9. Drive the operationalization of AI and ML solutions, ensuring models are deployed, monitored, maintained, and continuously improved.
10.



Proactively identify opportunities for innovation and continuous improvement by leveraging emerging AI technologies, customer feedback, and business insights.
11. Support solution development, proposal creation, pre-sales discussions, and capability presentations for prospective clients.
12. Mentor and coach data science teams, fostering a culture of innovation, experimentation, technical excellence, and business impact.

Required Skills and Experience
1. 10-14 years of overall experience, with 7+ years leading Data Science, AI, Advanced Analytics, or Machine Learning programs.
2. Strong experience delivering enterprise-scale analytics solutions across domains such as CPG, Retail, Healthcare, Pharma, Financial Services, or Manufacturing.
3. Expertise in Machine Learning, Statistical Modeling, Predictive Analytics, Optimization, Generative AI, and AI-driven decision systems.
4. Strong proficiency in Python, SQL, and modern analytical ecosystems.
5. Experience working with cloud platforms such as AWS, Azure, or GCP , including AI/ML services and MLOps capabilities.
6. Experience building and deploying machine learning models using frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar technologies.
7. Strong understanding of Data Engineering concepts, data pipelines, data modeling, and large-scale distributed computing platforms such as Spark and Databricks.
8. Experience establishing and scaling MLOps frameworks, model governance, model monitoring, and AI lifecycle management practices.
9. Demonstrated experience managing multiple delivery teams and leading large-scale analytics transformations.
10. Strong problem-solving skills with the ability to break down complex business challenges into structured analytical frameworks.
11. Experience managing program risks, stakeholder expectations, resource planning, budgeting, and change management.
12.



Ability to influence senior stakeholders and drive alignment across business, technology, and analytics teams.
13. Excellent communication, storytelling, and executive presentation skills.
14. Experience supporting pre-sales activities, solution architecture discussions, effort estimation, and proposal development.
15. Strong people leadership experience, including hiring, mentoring, performance development, and capability building.

Business & Client Leadership
- Develop a deep understanding of client business processes, industry challenges, and growth objectives to ensure analytics initiatives drive measurable outcomes.
- Partner with business leaders to identify strategic opportunities where AI, Machine Learning, and Advanced Analytics can accelerate decision-making and business growth.
- Serve as a trusted advisor to clients by translating business priorities into scalable data science and AI solutions.
- Drive adoption of analytics products and AI capabilities by ensuring alignment with business goals, operational processes, and user needs.

Account Growth & Stakeholder Management
- Build and maintain strong relationships with senior client stakeholders, acting as the primary point of contact for analytics and AI delivery initiatives.
- Identify opportunities for account expansion, new use cases, cross-sell opportunities, and innovation-led engagements.
- Collaborate with account management and sales teams to support revenue growth through delivery excellence and thought leadership.
- Support business development efforts through capability demonstrations, solution design, proposal development, and executive presentations.

Organizational Contribution
- Contribute to organizational growth through capability building, mentoring, hiring, and developing future analytics leaders.
- Drive innovation initiatives across AI, Generative AI, Machine Learning, and Advanced Analytics practices.
- Establish and promote best practices, frameworks, reusable assets, accelerators, and delivery methodologies across the Data Science organization.
- Represent the organization through thought leadership, industry forums, client workshops, and strategic consulting engagements.

📌 Data Science Delivery lead (Bengaluru)
🏢 MathCo
📍 Bengaluru