Data Scientist

Senior Data Scientist – Key Requirements

1. 5–8 years of hands-on experience in data science, with a strong track record of delivering production-grade solutions in business environments.
2. Deep expertise in traditional machine learning techniques, including time series forecasting (e.g., ARIMA, SARIMA), regression models, and other statistical methods applied to real-world datasets.
3. Proven experience designing and implementing optimization models (e.g., linear programming, mixed-integer programming, heuristics) to solve complex business problems such as demand planning, inventory optimization, or resource allocation.
4. Recent, demonstrable experience working on Generative AI initiatives, including LLM-based solutions and agentic workflows (e.g., autonomous agents, multi-step reasoning pipelines, tool-augmented AI systems).
5. Hands-on experience in designing, deploying, and operationalizing agentic workflows in production environments, including orchestration, tool integration, monitoring, and performance optimization of AI-driven agents.
6. Strong domain knowledge in Consumer-Packaged Goods (CPG), with hands-on experience in at least one functional area: Sales (e.g., demand forecasting, pricing), Finance (e.g., revenue/margin analytics), or Supply Chain (e.g., planning, logistics, inventory).
7. Ability to translate business problems into scalable analytical and AI-driven solutions, partnering closely with cross-functional stakeholders such as product managers, engineers, and business teams.
8. 100% hands-on role with active involvement in data exploration, model development, evaluation, deployment, and continuous improvement.
9. Proficiency in Python and relevant data science ecosystems (e.g., pandas, scikit-learn, statsmodels, PyTorch/TensorFlow), along with experience in cloud platforms and MLOps practices.