We are seeking a highly skilled Senior Machine Learning
Architect / Senior ML Individual Contributor to design and build a
production-grade, repeatable system for optimal store–SKU model stock
distribution for a national brick
‑
and
‑
mortar retailer (1,200+ stores,
~300 SKUs).

In this role, you will break the limitations of current tier
‑
based
forecasting by architecting a machine
‑
learning
‑
driven
optimization framework that captures rich, multi
‑
dimensional signals to localize
demand and improve SKU
‑
store alignment.

You will own the full lifecycle—from translating business
objectives into measurable optimization targets, to deploying containerized
solutions in production, to validating incremental lift through experiments.
You will operate with architectural authority, functioning as a senior IC who
can turn whiteboard concepts into fully deployed systems that merchandising and
supply
‑
chain
teams trust.

Responsibilities

Core Responsibilities

• 
  Architect
  end
  ‑
  to
  ‑
  end machine learning systems
  for high
  ‑
  dimensional retail demand modeling.
• 
  Design
  and build production
  ‑
  grade Python ML pipelines
  that retrain and adapt automatically.
• 
  Develop
  and test advanced forecasting approaches including hierarchical
  forecasting, gradient boosting, time
  ‑
  series models, and hybrid ML
  techniques.
• 
  Engineer
  complex feature pipelines integrating regional, demographic, climate,
  historical sell
  ‑
  through, promotional, and behavioral signals.
• 
  Design
  allocation or constrained optimization logic to convert demand forecasts
  into store
  ‑
  SKU model stock targets.
• 
  Validate
  model performance through backtesting, live pilots, and controlled
  experiments demonstrating measurable lift.
• 
  Deploy
  solutions in containerized production environments.
• 
  Work
  cross
  ‑
  functionally to translate ambiguous business
  problems into measurable outputs aligned with stockout reduction, model
  ‑
  stock
  accuracy, and sales lift.
• 
  Document
  methodology clearly and rigorously for leadership and cross
  ‑
  functional
  stakeholders.

Success Indicators

• 
  Forecast
  ‑
  based
  initial stock models that materially outperform current baselines.
• 
  A
  robust, repeatable pipeline that recalibrates and adapts seamlessly.
• 
  Quantifiable
  reduction in stockouts and improved sell
  ‑
  through.
• 
  A
  trusted system used by merchandising and supply
  ‑
  chain
  teams.

Requirements

Required Experience

• 
  7+
  years in applied machine learning, data science, or related fields.
• 
  Proven
  experience building multi
  ‑
  dimensional forecasting
  systems (e.g., store
  ‑
  SKU, geo
  ‑
  segmented).
• 
  Strong
  background in demand forecasting, inventory optimization, or retail
  analytics.
• 
  Production
  deployment experience in containerized environments.
• 
  Deep
  proficiency in Python and modern ML frameworks.
• 
  Experience
  working with large, structured datasets at scale.
• 
  Demonstrated
  ability to take solutions from whiteboard to production.

Strongly Preferred

• 
  Retail
  or supply
  ‑
  chain domain expertise.
• 
  Experience
  with hierarchical time
  ‑
  series forecasting.
• 
  Experience
  building allocation or optimization layers atop forecasting models.
• 
  Familiarity
  with experimentation frameworks (A/B testing, pilot rollouts).
• 
  Background
  in consulting or startup environments with high ambiguity and fast
  iteration.

Work Timing

US Central Standard Time, Remote from anywhere in India

Hours per week

40

Duration of Contract

120 Days

Application Process

Please visit
Jobs
at Mindverse Consulting Services Private Limited
and locate the
applicable job title. Read the JD in details and Click "I'm
Interested" and fill out accordingly.

Attach your CV and any other document you deem fit along
with the "Screening Questions" which is mandatory. Please be specific
and detailed. Note these questions are from the custom to evaluate your
candidature.

Any vague or inconclusive answer will not be considered.

Incase of any query, feel free to reach out to
career@mindverseconsulting.com