Data Scientist

Key Responsibilities

• Develop, deploy, and maintain machine learning and statistical models that power automated, scalable AI solutions.

• Build end-to-end automated AI pipelines, including data ingestion, feature engineering, model training, deployment, and continuous monitoring.

• Write clean, efficient Python code and build distributed data processing workflows in Azure Databricks using Spark.

• Use SQL across Snowflake and Azure data platforms to extract, transform, join, and analyze large datasets.

• Apply applied statistics, including hypothesis testing, regression modeling, experimental design, and probability, to support data-driven decisions.

• Integrate disparate data tables and sources to create a comprehensive 360 view of the customer, including support for near-time or real-time data updates.

• Design insightful Tableau dashboards and visualizations for both technical and business audiences.

• Work closely with stakeholders to translate business needs into analytical solutions that drive measurable outcomes.

• Explore and operationalize emerging AI/ML techniques, such as LLMs, NLP, embeddings, and generative AI.

• Ensure high standards of data quality, governance, and responsible AI throughout all modeling workflows.

• Work within and across the Azure ecosystem, including Azure Data Lake, Azure Machine Learning, Azure Data Factory, and related services. Required Qualifications

• Advanced degree (Masters or PhD) in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related analytical field.

• Strong proficiency in Python (pandas, NumPy, scikit-learn, PySpark).

• Expert-level SQL skills and experience with Snowflake in production environments.

• Hands-on experience with Azure Databricks, Spark, and Delta Lake.

• Broader experience with Azure cloud services such as Azure Data Lake, Azure Machine Learning, and Azure Data Factory.

• Experience building or contributing to automated AI/ML solutions.

• Proficiency in applied statistical methods, including regression, statistical testing, sampling, and model evaluation.

• Advanced experience in data visualization and dashboard development using Tableau.

• Ability to integrate data from multiple sources to form unified analytical views ideally with real-time or streaming data components.

• Strong business acumen, with the ability to convert insights into strategic recommendations.

Preferred Qualifications:

• Experience with MLOps, CI/CD pipelines, or ML model monitoring frameworks.

• Familiarity with deep learning (TensorFlow, PyTorch) or generative AI frameworks.

• Experience with data streaming technologies (e.g., Azure Event Hub, Kafka).

• Knowledge of LLM fine-tuning, vector search, and modern AI architectures (e.g., RAG).

• Ability to communicate complex concepts through compelling data stories.