Job Title : Lead Data Scientist Demand Forecasting.

Location : [Bengaluru Hybrid].

Employment Type : Full-Time.

Department : Data Science / Supply Chain Analytics.

Our Client is AI Product company (Startup).

Notice Period : Immediate Joiner / 30 days.

As a Lead Data Scientist, you will work on high-impact forecasting problems, develop scalable models, and collaborate closely with product, engineering, and customer-facing teams. Your work will directly influence key business decisions across inventory, pricing, and logistics.

Key Responsibilities

• Understand business objectives and conduct deep exploratory data analysis to identify the best forecasting strategies.
• Develop and train machine learning and deep learning models on large-scale time series datasets.
• Perform descriptive analytics and data visualization to provide actionable insights to stakeholders.
• Design, implement, and optimize end-to-end data science pipelines for demand forecasting, inventory management, and price
  
  

optimization.

• Collaborate with cross-functional teams to deploy models and monitor performance in production.
• Analyze model accuracy across different segments to ensure fairness and robustness.
• Present insights and recommendations to internal and external stakeholders.
• Contribute to research and innovation efforts in forecasting and optimization You Bring :
• 7+ years of experience in a data science or machine learning role, preferably with exposure to demand forecasting or supply chain optimization.
• Bachelor's or Masters degree in Statistics, Mathematics, Computer Science, Physics, Economics, or a related field.
• Strong expertise in time series modeling, regression, and deep learning.
• Hands-on experience with Python (NumPy, pandas, Scikit-learn, PyTorch/TensorFlow), SQL, and data visualization tools.
• Proven ability to build and scale end-to-end machine learning pipelines.
• Experience with A/B testing, hypothesis-driven development, and statistical analysis.
• Ability to clearly communicate technical insights to non-technical stakeholders.
• Strong problem-solving and analytical thinking Bonus :
• Industry experience in CPG, FMCG, or retail (because real-world demand is volatile and driven by many external factors like promotions, holidays, supply issues).
• Experience dealing with noisy, large-scale datasets and seasonality.
• Hands-on with ML Ops tools or cloud platforms (AWS/GCP/Azure).
  
  

(ref:hirist.tech)