CPG Domain & Data Insights Consultant

In the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as below:

• Develop data preparation tasks, while identifying patterns or anomalies.
• Ensure data readiness for advanced modeling.
• Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production‑ready solutions.
• Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in best practices.
• Design and develop predictive models and data‑driven analyses to address business challenges.
• Build, evaluate, and deploy models, standardize code, and contribute to knowledge management.
• Leverage tools like SAS and R/Python to create reusable customizations for non‑ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost‑effective solutions.
• Define analytics problems for projects; execute visualization, analysis, and predictive modeling under guidance.
• Proactively maintain models and implement improvements for accuracy and reliability.
• Apply governance controls to mitigate risks and ensure compliance.
• Analyze performance trends, recommend improvements, and document discrepancies for escalation.
• Maintain comprehensive documentation standards, while participating in knowledge transfer sessions.
• Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models.
• Apply the predefined quality measurement framework at an individual task level in the project.
• Deploy complex analytics tools or multi‑system integration, while validating deployment success.
• Participate in developing scripts or templates for repeated deployments tasks.
• Contribute to analytic solutions, IP asset creation, and training initiatives.
• Contribute to thought leadership such as papers, innovative non‑ML, ML, deep learning or LLM models, and proofs of concepts.
• Participate in and deliver analytics training, while contributing to content creation.
• Provide input for segment and unit‑level business plans.

• Deliver scalable, high‑quality analytics solutions aligned to business needs.
• A knack for optimization, deployment and performance improvement of models.
• The ability to drive innovation through advanced analytics, automation and thought leadership.
• Enable team growth through knowledge sharing, training and standardization.
• Support business planning with data‑driven insights.