Company Overview

Logile is the leading retail labor planning, workforce management, inventory management and store execution provider deployed in thousands of retail locations across North America, Europe, Australia, and Oceania.

Our proven AI, machine-learning technology and industrial engineering accelerate ROI and enable operational excellence with improved performance and empowered employees. Retailers worldwide rely on Logile solutions to boost profitability and competitive advantage by delivering the best service and products at optimal cost.

From labor standards development and modeling to unified forecasting, storewide scheduling, and time and attendance, to inventory management, task management, food safety, and employee self-service — we transform retail operations with a unified store-level solution. Gain the Advantage with The Logic of Retail. One Platform for store planning, scheduling and execution.

For more information, visit www.logile.com

We focus on solving real business problems using data science, analytics, and machine learning — across domains like marketing, pricing, customer intelligence, and forecasting.

Job Summary:

We are looking for a Senior Data Scientist who can translate business problems into analytical solutions and deliver measurable outcomes.

This is not a purely academic role — you will:

Work on real datasets
Build usable models
Deliver business insights and decision frameworks

Key Responsibilities:

Problem Framing & Business Understanding

Translate ambiguous business problems into structured analytical approaches
Define success metrics aligned with business goals

Data Analysis & Feature Engineering

Perform exploratory data analysis (EDA)
Build meaningful features from structured and unstructured data
Handle data quality issues pragmatically

Model Development

Build and validate models for:
Forecasting
Classification
Recommendation systems
Hybrid models, Stochastic understanding
Deep learning models & ability to create hybrid versions of them
Focus on interpretability + performance

Communication & Storytelling

Translate model outputs into business insights
Create dashboards, reports, and presentations
Work with stakeholders across functions

Collaboration with Engineering

Work with MLEs to productionize models
Ensure models are practical and deployable

Job Location & Schedule:

This job is an onsite job at Logile Bhubaneswar Office.
It is expected that the selected candidate will be available to work with some hours of overlap with US working times

Required Skills & Experience:

5-10 years in Data Science / Analytics roles
Experience solving real-world business problems

Technical Skills

Core

Python / R
Strong SQL
Experience with:
Scikit-learn
Family of trees
Stats-models
Transformer based models
Stochastic models
Understanding of advanced statistics
Understanding of parametric/non-parametric division
Understanding of frequentist and Bayesian modelling techniques.
Advanced Feature engineering
Ability to work with Data bases – Analytics ( Realtime & Batch ) along with vector data bases.

MLOps & Systems

Experience with:
Docker
REST APIs (FastAPI / Flask)
Cloud platforms (AWS / GCP / Azure)
Familiarity with feature stores and model registries

Data

Strong SQL skills
Experience with data pipelines and ETL workflows

System Thinking

Understanding of:
Latency vs accuracy trade-offs
Batch vs real-time systems
Failure handling and retries

Preferred Skills

Experience with LLM-based systems (RAG pipelines, embeddings)
Exposure to vector databases (FAISS, Pinecone, Weaviate)
Experience with streaming systems (Kafka)

Success in This Role Looks Like:

ML models are deployed and used in production
Pipelines are stable, monitored, and reproducible
Reduced time from experimentation → production
Minimal firefighting due to robust systems

Compensation and Benefits:

The compensation and benefits associated for this role is benchmarked against the best in industry and job location.
Standard shift: 1 PM – 10 PM (shift allowance applicable as per role).
Shifts starting after 4 PM: Eligible for food allowance/subsidized meals and cab drop.
Shifts starting after 8 PM: Eligible for cab pickup as well.

Logile, Inc.

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