About Logile

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.