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Machine Learning Engineer – Pricing Optimizer Development

Machine Learning Engineer – Pricing Optimizer Development

DigitideBengaluru, Karnataka, India
6 days ago
Job description

Location - Bengaluru (onsite)

Notice Period - able to join within 15 to 20 days

Budget - Open

We are looking for a skilled ML Engineer to design and build a robust, interpretable, and scalable optimization engine that enables data-driven pricing decisions. The engine will leverage SKU-level demand, elasticity, and profitability data to recommend optimal pricing strategies based on business goals.

Key Responsibilities

  • Refactor and enhance the existing optimization logic for speed, scalability, and modularity.
  • Model price-volume relationships using elasticity inputs at SKU and brand levels.
  • Develop optimization logic using constrained techniques (e.g., linear / quadratic programming).
  • Integrate business rules and constraints such as price bounds, SKU / brand-level caps, and TDP limits.
  • Enable scenario-based optimization with user-defined goals (e.g., maximize profit or volume).
  • Support multi-brand optimization without interdependency between SKUs and brands.
  • Collaborate with cross-functional teams to validate model behavior and outcomes.

Inputs You’ll Work With

  • SKU-level data : volume, elasticity, profitability, TDP, and price bounds.
  • Business rules : brand-level caps, SKU exclusions, optimization targets.
  • Deliverables

  • Modular Python-based optimization engine.
  • JSON-based input / output support for seamless integration.
  • Logging and fallback mechanisms for infeasible constraints.
  • Unit tests and validation with historical data.
  • Tech Stack & Skills

  • Proficient in Python, especially NumPy, Pandas, SciPy or Pyomo / CVXOPT.
  • Experience with constrained optimization techniques.
  • (Preferred) Background in price optimization, demand modeling, or econometrics.
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    Machine Learning Engineer • Bengaluru, Karnataka, India

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