Job
Description
Hiring for: A leading well funded B2B SaaS company serving global CPG clients in the supply chain domain. Part of one of the largest global Analytics consulting firms. Positions: 2 Location: Bangalore (Hybrid) Experience: Min. 6 years in DS, overall could be more Preferred Joining: Immediate to 30 days Reporting to: Director of Data Science Direct Reports: Zero (this is an IC role) Salary: 50L+ range based on fitment and skills Overview: As a Lead Data Scientist, you will be instrumental in shaping the company's next-generation AI-driven demand planning and optimization products. You will lead the design and deployment of data science solutions that power the company's core decision intelligence engine driving measurable business impact for our global clients. From problem scoping to model deployment, you will own the full data science lifecycle and work closely with cross-functional teams to integrate intelligence into key decision-making workflows. Role & Responsibilities: Conduct exploratory data analysis to uncover trends, patterns, and insights from complex datasets Design, train, and deploy machine learning and deep learning models for time series use cases such as demand forecasting, inventory management, and pricing Extract data insights, create visualizations, and communicate findings to technical and non-technical stakeholders Build and maintain data science pipelines for model development, deployment, monitoring, and updates Collaborate with engineering, product, and business teams to integrate models into production systems and align with client goals Research and prototype new algorithms and modelling techniques to improve solution performance Monitor and evaluate model performance and iterate based on finding Requirements: 6+ years of experience in data science, machine learning, or analytics roles Experience with time series analysis, forecasting, and predictive modelling. Proficient in Python (NumPy, pandas, Scikit-learn, TensorFlow, or PyTorch), SQL, and Excel Familiarity with deploying machine learning solutions and managing model lifecycle Ability to work with engineering and product teams to scope and deliver projects Ability to explain modelling choices, data assumptions, and outcomes to stakeholders Exposure to statistical methods, optimization, and model monitoring frameworks Prior experience working in CPG, FMCG, or retail industries is a plus
