About the role
Job Title Data Science Lead - India Distribution
Business Unit Global Supply Chain
Job Grade Location : Sun House, Mumbai
At Sun Pharma, we commit to helping you “ Create your own sunshine”— by fostering an environment where you grow at every step, take charge of your journey and thrive in a supportive community.
Are You Ready to Create Your Own Sunshine?
As you enter the Sun Pharma world, you’ll find yourself becoming ‘Better every day’ through continuous progress. Exhibit self-drive as you ‘Take charge’ and lead with confidence. Additionally, demonstrate a collaborative spirit, knowing that we ‘Thrive together’ and support each other’s journeys.”
Key Responsibilities
- Lead and manage the end-to-end data science function for global supply chain operations
- Build, mentor, and scale a high-performing data team (data analysts, data scientists, and engineers)
- Own and enhance distributor ordering and inventory optimization algorithms
- Drive continuous improvement, scalability, and accuracy of ordering and replenishment models
- Lead data and analytics ownership for Kinaxis, including integration, data validation, and ongoing optimization of planning models
- Collaborate with planning, business, and IT teams to ensure effective adoption and performance of Kinaxis
- Translate complex business problems across demand planning, inventory, logistics, and procurement into analytical solutions
- Develop and deploy advanced analytics, statistical models, and data-driven frameworks to improve supply chain KPIs
- Design and oversee data pipelines, data models, and scalable analytics solutions
- Ensure high standards of data quality, governance, and accessibility across systems
- Partner closely with IT teams to align on data architecture, cloud infrastructure (Azure/AWS), and system integrations
- Work with large structured and unstructured datasets from multiple enterprise systems and data lakes
- Drive adoption of analytics solutions by collaborating with global stakeholders and leadership teams
- Present insights and recommendations clearly to senior management
- Continuously identify opportunities for automation and optimization using Python, SQL, and VBA
Technical Skills
- Expert proficiency in Python for data analysis, modeling, and automation
- Advanced SQL skills for data extraction and transformation
- Strong working knowledge of VBA for automation and legacy systems
- Hands-on experience with Azure or AWS cloud platforms
- Experience with data lakes, ETL processes, and large-scale data handling
Behavioral Competencies
- Strong leadership and stakeholder management skills
- Excellent analytical and problem-solving ability
- Strong communication skills (technical and non-technical audiences)
- Ability to work in a fast-paced, global, cross-functional environment
Travel Estimate 10–20% depending on stakeholder engagement
Job Requirements Educational Qualification
- Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, or a related field
Experience
- 10-12+ years of experience in data science, analytics, or related roles
- 3–5+ years of experience leading teams
- Strong experience in global supply chain or operations analytics
Your Success Matters to Us At Sun Pharma, your success and well-being are our top priorities! We provide robust benefits and opportunities to foster personal and professional growth. Join us at Sun Pharma, where every day is an opportunity to grow, collaborate, and make a lasting impact. Let’s create a brighter future together!
Disclaimer: The preceding job description has been designed to indicate the general nature and level of work performed by employee within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees as assigned to this job. Nothing herein shall preclude the employer from changing these duties from time to time and assigning comparable duties or other duties commensurate with the experience and background of incumbent(s).
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