Associate Specialist Data Science

• Drive product design and ensure consistent execution of product lifecycle processes from concept to launch, ensuring user-centric solutions
• Define and monitor Product Success metrics and criteria at incremental product development phases, and product adoption
• Facilitate 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 and success stories to key stakeholders
• Lead creation of comprehensive playbook and training material to standardize and share SOPs with product development and other analytics teams
• 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
• Lead creation of benchmark techniques being deployed across multiple product development strategies
• Identify cutting-edge trends and best practices in the market to improve product positioning
• Qualifications
• Education & Work Experience Requiremen ts:
• Bachelor s degree (in Engineering or related field, such as Computer Science, Data Science, Statistics, Business, etc.) with at least 6+ years relevant experience
• Master s degree (relevant field like Computer Science, Economics, Statistics, Mathematics, Operational Research) with 3+ years work 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
• Experience in Software Development and Engineering, and Analytics Delivery
• Expertise in developing scalable, secure, and modular product architectures
• Proficiency in designing & implementing data structure, pipeline & architecture
• Hands-on experience with product roadmaps, Agile methodologies and backlog management, ensuring iterative and incremental product improvements
• Strong problem solving, critical thinking, business analysis and quantitative skills
• Story Boarding - Ability to effectively communicate proposals to key stakeholders
• Understanding of end-to-end Pharma commercial landscape
• 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, A/B testing, propensity score matching etc.
• Experience working with healthcare, financial, or enterprise SaaS products
• Experience with Marketing Mix Modeling and optimization with underlying concepts such as ad-stock, decay, interaction and halo effects etc.