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Urgent! Machine Learning Engineer – Pricing Optimizer Development Job Opening In Bengaluru – Now Hiring Digitide

Machine Learning Engineer – Pricing Optimizer Development



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.


Required Skill Profession

Computer Occupations



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