Senior Data Scientist

The Data Science Domains Department powers business-critical decision-making across four key areas of enterprise operations. We build and deploy AI-driven features that transform how business leaders understand and act on complex data challenges in their specific domains.

Each domain has distinct requirements, challenges, and opportunities—but all share the mission of delivering real-time, actionable AI insights that drive measurable business impact.
Our Four Domains:

• Finance (FIN): We enable smarter, faster financial decision-making across the enterprise by partnering with Finance teams to improve forecasting accuracy, planning agility, and financial transparency through AI-driven solutions. We tackle volatile revenue and demand signals, large-scale multi-dimensional forecasting, and resource allocation under uncertainty, while ensuring models remain explainable and actionable. Our work moves Finance beyond reactive reporting toward proactive data-driven decision-making, powered by production-grade ML systems at enterprise scale.

• Manufacturing & Supply Chain (M&S): We optimize the end-to-end manufacturing and supply chain with cutting-edge AI. Our team works closely with supply chain champions across Fortune 500 companies to drive impact: from helping pharmaceutical companies to avoid out-of-stocks to reducing machine breakdown in consumer good factories. Our solutions consist of a mix of statistical, machine learning, GenAI, Knowledge Graph, and agentic techniques to tackle challenges such as low signal demand forecasting, explainability for supply chain autonomy, and providing detailed actionable recommendations based on a mix of textual, image, and structured data.

• Research & Development (R&D): We are passionate about clinical operations and portfolio management. Our team partners closely with pharmaceutical and biotech companies to deliver innovative AI-driven solutions that optimize clinical trial recruitment and accelerate pipeline innovation. Some of the exciting use cases we’ve worked on include predicting patient enrollment, optimizing trial design, building knowledge graphs across the pharma ecosystem, and more.

• Cross-Functional (XF): this team addresses critical business areas that extend beyond the scope of our other specialized domains. We apply AI to diverse functions spanning procurement, people analytics, commercial operations, and more – developing solutions that transform these essential but often underserved areas. By focusing on these complementary business functions, we ensure our AI platform delivers comprehensive value across the entire enterprise, helping organizations unlock insights and efficiencies in every corner of their operations.

Responsibilities: 

• Build and maintain AI-driven features (forecasting, classification, regression, recommender systems, LLM-powered features) for business use cases
• Contribute to app features with guidance from mid/senior teammates; improve models, pipelines, and deliverables
• Present results and findings to your team; identify gaps and learn to explain the product and the AI behind it.
• Deliver assigned tasks autonomously and on time with clear ownership
• Have strong Python/SQL skills, basic MLOps knowledge (Airflow, MLflow, unit testing), and solid ML fundamentals
• Own features of the app; constantly improve models, pipelines, and monitoring to ensure robust production performance
• Communicate and align with internal stakeholders; identify opportunities and explain AI behind business outcomes
• Design end-to-end ML pipelines for small projects; mentor junior team members on technical topics
• Have comprehensive MLOps expertise, advanced Python/SQL skills, and domain specialization; enforce code quality standards across the team
• Own key features and projects; design and improve models, pipelines, and experimentation frameworks
• Lead 1+ major projects as AI lead with full accountability; break down work, assign tasks, and manage multiple workstreams with stakeholder alignment
• Communicate and align with internal/external stakeholders; turn business requirements into AI solutions; make speed vs. quality trade-offs
• Provide technical mentorship; set modeling standards and drive cross-functional delivery with PMs, engineers, and customers

• Strong Python/SQL skills for the recent 4+ years
• Having recent MLOps knowledge (Airflow, MLflow, unit testing)
• Solid ML fundamentals
• Define and own AI domain roadmaps
• Leadership skills
• Good spoken English level