Data Science - JD

Key Responsibilities

Work with data from multiple internal/external data sources and APIs including Hadoop clusters
Work with structured as well as unstructured data
Data wrangling for cleanup, handle missing data, standardize/scale data
Explore and analyze data using visualizations to uncover hidden patterns
Use ML techniques including linear/logistic regression, decision trees, classification, clustering, ensembles, text mining, social networking analysis to build models
Use these models to identify patterns and rules which help unearth business insights and aid in decision making

Education & Experience

Bachelor, Master's or PhD in Data Science, Computer Science, Statistics, Mathematics, or related quantitative field
3+ years of hands-on experience with NLP, recommendation systems, or generative AI

Technical Skills

Programming : Expert-level Python; proficiency in SQL, or Scala
ML Frameworks : PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers
NLP Libraries : spaCy, NLTK, Gensim, transformers
Big Data : Spark, Hadoop, or similar distributed computing frameworks
Cloud Platforms : AWS/GCP/Azure ML services and infrastructure
MLOps : Experience with model deployment, monitoring, and CI/CD pipelines

Databases : SQL and NoSQL databases, vector databases (Opensearch )

Deep understanding of transformer architectures and attention mechanisms
Experience with recommendation system architectures (matrix factorization, deep learning approaches)
Knowledge of information retrieval and search relevance
Familiarity with A/B testing and statistical significance testing
Understanding of ML interpretability and fairness considerations

Data Scientist