
AI Engineer / Data Scientist with 4+ years of experience building and deploying production ML and automation systems across retail and e-commerce. Proven track record integrating AI services with APIs, data pipelines, and cloud platforms (AWS, Snowflake, Azure) to deliver measurable business impact (19% revenue lift, 22% stock-out reduction, $2.3M annual savings). Strong in Python/SQL, ML systems, orchestration, and translating Sales/Marketing workflows into scalable AI solutions with monitoring and business impact metrics.
Programming Languages: Python, R, SQL, T-SQL, PowerShell, UNIX Shell Scripting, Java, Scala
Machine Learning & AI: Scikit-learn, XGBoost, TensorFlow, Keras, PyTorch, Prophet, PySpark, MLflow, Hugging Face
Agentic AI & Automation: Agent orchestration (LangChain/LangGraph or equivalent), RAG pipelines, tool/function calling, API integrations, workflow automation, prompt/context engineering, MCP (Model Context Protocol) concepts, vector databases (FAISS/Pinecone or equivalent)
Cloud Platforms & Services: AWS (S3, Glue, Redshift, EC2, EMR, SageMaker, Lambda), Azure, GCP, Snowflake
Big Data: Hadoop, Apache Spark, Kafka, Beam, Databricks, Dask, Hive, Flink
Databases: MySQL, PostgreSQL, Oracle, MS SQL Server, HBase, Teradata, MongoDB, Cassandra, BigQuery, Azure SQL
BI & Visualization: Tableau, Power BI, Matplotlib, Seaborn, Plotly, Looker
ETL & Orchestration: Apache Airflow, AWS Glue, NiFi, Talend, Informatica, SSIS, Data Factory
DevOps & MLOps: Git, GitHub, Bitbucket, Jenkins, Docker, Kubernetes, CI/CD, model deployment & monitoring
Statistics & Experimentation: A/B testing, hypothesis testing, time series, Bayesian methods, ANOVA
Ways of Working: Agile/Scrum, cross-functional stakeholder engagement