Description :

Role Overview :

We are seeking a highly experienced Data Science & AI Leader who can translate business vision into a scalable data science roadmap and successfully drive end-to-end AI and analytics programs for enterprise clients.

This role requires a rare blend of hands-on technical expertise, team leadership, strategic thinking, and client-facing capabilities.

The incumbent will act as a trusted advisor to client leadership, lead complex analytics engagements, mentor high-performing teams, and contribute to internal IP and product development initiatives.

Key Roles & Responsibilities :

Strategic Leadership & Roadmap Development :

- Translate high-level business objectives and abstract ideas into a clear, actionable data science and AI roadmap aligned with client goals.

- Define technology strategy, analytics architecture, and execution frameworks for client accounts.

- Guide implementation of the defined strategy across multiple concurrent projects and teams.

Client Engagement & Program Ownership :

- Own and manage end-to-end client AI and analytics programs in a fast-paced, evolving environment.

- Act as a trusted advisor to client IT and business leadership, influencing decision-making with data-driven insights.

- Understand complex business problem statements and propose scalable, high-impact analytics and AI solutions.

- Ensure consistent stakeholder communication, expectation management, and value realization.

Hands-on Data Science & Technical Excellence :

- Lead by example through hands-on contribution to complex data science problems when required.

- Discover actionable insights hidden in large, complex, and diverse datasets to drive measurable business outcomes.

- Design, develop, validate, and deploy machine learning and deep learning models across structured and unstructured data.

- Apply advanced statistical, data mining, and AI techniques to solve real-world business challenges.

Team Leadership & Mentorship :

- Lead, mentor, and manage cross-functional teams of data scientists, ML engineers, and analysts.

- Ensure project plans, milestones, and quality standards are met throughout the engagement lifecycle.

- Foster a culture of innovation, accountability, and continuous learning within the team.

Project & Delivery Management :

- Drive strong project management practices for complex analytics initiatives, including :

a. Effort and timeline estimation.

b. Risk identification and mitigation.

c. Resource planning and utilization.

- Take full ownership of delivery outcomes with a proactive, solution-oriented mindset.

- Build scalable engagement-level processes to improve turnaround time, accuracy, and delivery efficiency.

Internal Product & IP Development :

- Contribute to internal data science products, accelerators, reusable frameworks, and IP creation.

- Identify opportunities to standardize solutions and build repeatable assets across engagements.

Pre-sales & Business Enablement :

- Provide technical and solutioning inputs for sales and pre-sales activities, including proposals, solution design, and client presentations.

- Support business growth by articulating value propositions and demonstrating technical thought leadership.

Mandated Skills & Qualifications :

Education :

B.Tech / M.Tech

Experience :

- 10+ years of hands-on experience in applied Machine Learning, AI, and advanced analytics.

- Proven track record of delivering enterprise-scale analytics and AI solutions.

Technical Skills :

Strong experience in scientific programming and data engineering, including :

- Python, R, SQL, NoSQL.

- Spark and large-scale data processing frameworks.

Deep expertise in Python libraries and frameworks such as :

- NumPy, Pandas, Scikit-learn.

- TensorFlow / PyTorch.

- NLP and transformer-based models (e., BERT).

- Web scraping and data ingestion tools (e., Scrapy).

Strong exposure to cloud platforms such as AWS, Azure, or GCP, including ML and data services.

Data Science & AI Expertise :

Strong conceptual and practical understanding of :

- Machine Learning and Deep Learning algorithms.

- Statistical modeling and inference.

- Data mining and feature engineering.

Experience working with structured and unstructured data ecosystems (text, images, logs, etc.

Domain Expertise :

Demonstrated experience solving business problems in domains such as :

- Supply Chain.

- Manufacturing.

- CPG.

- Marketing and Customer Analytics.

Desired / Preferred Skills :

- Deep understanding of ML algorithms for common enterprise use cases across industries.

- Comfortable working with large-scale distributed computing environments.

- Experience collaborating with sales and leadership teams for solutioning and deal support.

- Strong ownership mindset with the ability to work independently with minimal supervision.

- Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.