About
Data Scientist with 4+ years of experience delivering production ML and analytics solutions in marketing domains, driving measurable business impact including ~$400K in campaign revenue. Strong in Python and SQL, with hands-on experience in machine learning, data pipelines, and AWS-based analytics. Skilled in translating business problems into data-driven solutions, with hands-on exposure to LLMs, RAG, and AI-powered analytics applications.
Skills & Expertise (33)
Work Experience
Data Scientist
Lands’ End Incorporated
Aug 2021 - Jan 2024
Owned the end-to-end lifecycle of household-level targeting models for catalog campaigns, delivering scoring outputs adopted by marketing operations and supporting ~$400K in campaign revenue during active deployment. Executed AWS-based analytics pipelines (Airflow, Glue, S3) to generate feature and target datasets supporting model training and production scoring. Evaluated Logistic Regression, Random Forest, and XGBoost using cross-validation, ROC-AUC, and lift/gains analysis, leveraging MLflow for experiment tracking and benchmarking against BAU targeting strategies. Presented model performance insights and recommendations to stakeholders, influencing campaign targeting decisions and adoption of model-driven approaches. Performed root-cause analysis to resolve inconsistencies in campaign performance metrics across Power BI dashboards by building a POC dataset in Redshift to standardize CAC, ROAS, and LTV, ensuring consistent reporting. Led data validation for Netezza → Redshift migration by developing reconciliation checks across multiple tables (8+), ensuring data consistency and minimizing discrepancies in reporting outputs prior to cutover. Refactored legacy SAS/R reporting workflows into Python pipelines, reducing manual effort by ~30–40% while improving maintainability and standardizing cross-functional reporting processes.
Data Analyst
ICONMA LLC (Client-CNH Industrial)
Oct 2020 - Jul 2021
Built a Python and SQL-based customer matching solution using record linkage techniques to reconcile legacy and new records, creating a unified dataset for segmentation and retention analysis, improving customer retention by ~15%. Designed ETL workflows by extracting customer survey data from LimeSurvey, transforming and standardizing attributes using Python and SQL, and loading clean datasets into SQL Server for downstream reporting and analytics.
Applied Analytics Trainee (Unpaid)
Illinois Institute of Technology
Mar 2020 - Oct 2020
Built a customer churn prediction model using Python (Pandas, scikit-learn) and SQL, testing ensemble methods and basic neural network models for retention analysis, and deployed it using lightweight Python Flask app on AWS EC2.
Software Engineer
Tata Consultancy Services (Client-AbbVie)
Oct 2019 - Mar 2020
Performed root-cause analysis on data and document integration issues between Salesforce and Veeva Vault, resolving recurring failures and saving ~$30K annually.
Education
M.S. in Computer Science - Illinois Institute of Technology
2017 - 2019 · Afghanistan
B.S in Computer Science & Engineering - Dr Ambedkar Institute of Technology
2013 - 2017 · Afghanistan
Certifications
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Skills (33)
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