Skills
Programming & Data Science:
Python (Pandas, NumPy, Scikit-learn, TensorFlow, Matplotlib), R, SQL, PySpark
Machine Learning model development and evaluation
Data visualization using Tableau, Power BI, and Seaborn
Jupyter Notebooks, VS Code
ETL & Data Engineering:
Building production-grade ETL pipelines using SQL, AWS Lambda, S3, and GCP (BigQuery, Cloud Functions)
Data pipeline automation and orchestration
Data validation and quality assurance processes
Cloud & Big Data Platforms:
Amazon Web Services (AWS): S3, Lambda, EC2
Google Cloud Platform (GCP): BigQuery, Cloud SQL, Cloud Functions, Cloud Scheduler
Hadoop, Snowflake, Amazon Redshift
Tools & Integration:
GitHub, Jira, Confluence, Azure DevOps
Experience developing plugins/custom components for enterprise tools
Exposure to APIs, RShiny, and Dash for custom app development
Communication & Collaboration:
Strong written and verbal communication skills; able to convey technical concepts to non-technical audiences
Experience delivering training and consultative support to internal and external stakeholders
Proven track record of cross-functional teamwork and customer-focused problem solving
About
Results-driven Associate Data Scientist with 4+ years of experience in analytics, data engineering, and machine learning across healthcare and technology sectors. Proven ability to build and deploy end-to-end data solutions using Python, SQL, AWS, and GCP, while effectively translating complex data into actionable business insights. Adept at creating predictive models, automating ETL pipelines, and developing interactive dashboards with Power BI and Tableau. Strong communicator with experience in client-facing roles, technical training, and cross-functional collaboration. Passionate about empowering teams through data and continuously learning innovative tools and techniques in the AI ecosystem.
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