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