Associate Manager Data Science

• Support product design and ensure consistent execution of product lifecycle processes from concept to launch, ensuring user-centric solutions
• Support defining and monitoring Product Success metric at incremental product development phases
• Participate in cross-functional collaboration with engineering, marketing, and sales teams to align on product goals and roadmap planning for automation/improvements as per business needs
• Effectively communicate progress, challenges, learning to key stakeholders
• Gather user feedback to refine product features. Evaluate technical feasibility of new product features and enhancements. Ensure smooth handoff of product requirements to development teams
• Support design and development of benchmark techniques being deployed across multiple product development strategies
• Work with other members in team to create and present comprehensive playbook and training material to standardize and share SOPs with product development and other analytics teams
• Support in identification of cutting-edge trends and best practices in the market to improve product positioning

• Bachelor s degree (in Engineering or related field, such as Computer Science, Data Science, Statistics, Business, etc) with at least 3+ years relevant experience
• masters degree (relevant field like Computer Science, Economics, Statistics, Mathematics, Operational Research) with 2+ years work experience
• 1 + Years of Product management or Software development experience

Skillset:

Candidates must have -

• Strong proficiency in Python, SQL, and cloud-based environments (AWS, GCP, or Azure) is a must. Experience with APIs, microservices, and DevOps practices is a plus
• Understanding of Software Development Lifecycle and Agile methodologies
• Exposure to product roadmap design and product management
• Understanding of data structure, pipeline & architecture
• Strong problem solving, business analysis and quantitative skills
• Story Boarding - Ability to effectively communicate proposals to key stakeholders
• Understanding of analytics tools like Tableau, PowerBI , Dataiku etc
• Candidates are desired but not mandatory to have -
• Experience with data science principles, machine learning (supervised and unsupervised) and GenAI algorithms, test-control analysis, propensity score matching etc
• Understanding of Pharma commercial landscape will be a plus
• Experience with Marketing Mix Modeling and optimization with underlying concepts such as ad-stock, decay, interaction and halo effects etc

Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Machine Learning, Software Development, Stakeholder Relationship Management, Waterfall Model