Experience: 7–9 Years
Location: Remote
Type: Contract Working Model:
● Fully Remote engagement
● Only bench profiles to be considered
● Profiles must be shared in Word format
● Work closely with Data Science, Engineering, Product, and Business stakeholders
● Design and deploy recommendation and personalization solutions at scale
Key Responsibilities:
● Design, build, deploy, and optimize recommendation systems for large-scale platforms
● Develop personalized recommendation engines using collaborative filtering, content-based, hybrid, and deep learning approaches
● Implement and enhance recommendation models such as ALS, SVD, FM, DeepFM, Wide & Deep, and session-based recommendation systems
● Process and analyze large-scale datasets using PySpark, Hive, and Delta Lake
● Build and manage feature engineering pipelines and feature stores
● Develop, monitor, and maintain machine learning pipelines using MLOps best practices
● Collaborate with product, engineering, and business teams to improve customer engagement and personalization
● Create dashboards, reports, and business insights using visualization tools
● Evaluate model performance and continuously improve recommendation accuracy and scalability
Required Skills:
● 7–9 years of hands-on experience in Data Science
● Minimum 3 years of experience building and deploying Recommendation Systems at scale
● Mandatory domain experience in Retail, e-Commerce, or FMCG
● Strong Python programming expertise
● Hands-on experience with:
○ Scikit-learn
○ PyTorch
○ TensorFlow
○ LightFM
○ Surprise
● Strong understanding of recommendation frameworks:
○ ALS
○ SVD
○ Factorization Machines (FM)
○ DeepFM
○ Wide & Deep
○ Session-based Recommendation Models
● Experience with large-scale data processing using:
○ PySpark
○ Hive
○ Delta Lake
● Experience with Feature Stores such as Feast, Tecton, or similar
● Experience with MLOps platforms and tools:
○ MLflow
○ Kubeflow
○ SageMaker
○ Vertex AI
● Database expertise in PostgreSQL, Cassandra, Redis, or similar technologies
● Strong visualization, storytelling, and stakeholder communication skills
● Experience with Tableau, Power BI, or Python-based visualization libraries
Preferred Skills:
● LLM-based Recommendation and Personalization Systems
● Knowledge Graphs and Entity Resolution
● Omnichannel Retail experience (Online, Offline, POS, Loyalty Data)
● Open-source contributions or published research in Recommendation Systems, NLP, or Machine Learning
● Experience in consulting organizations or product-led analytics companies Educational Qualification: B.Tech / M.Tech / M.Sc / MBA in Computer Science, Statistics, Mathematics, or related quantitative disciplines from reputed institutions
Duration: To Be Confirmed
Pay: ₹780,000.00 per year
Work Location: Remote
