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
Job Summary
We are looking for a 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
2–5 years in Data Science / Analytics roles
Experience solving real-world business problems
Technical Skills
Core
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.
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