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MANITEJA REDDY JULAKANTI

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Newark, Delaware, United States

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Jobs verified_user 0% verified
  • Community Dreams Foundation
    Data Scientist
    Community Dreams Foundation
    Jul 2025 - May 2026 (11 months)
    • Analyzed workforce training, community program, outreach, and service adoption data with Python, SQL, Pandas, and Snowflake to uncover engagement gaps and help teams prioritize support for underserved participant groups.
    • Built classification models in Scikit-learn using feature engineering, cross-validation, and behavioral data to flag participants at risk of drop-off, improving early intervention targeting by 32%.
    • Prepared model-ready datasets from attendance, training progress, outreach response, and engagement records using PySpark, Spark SQL, and Databricks, reducing manual data preparation effort by 28%.
    • Segmented participant behavior through clustering, data mining, Python, Pandas, and Scikit-learn to group serv
  • Gilead Sciences
    Data Science Engineer
    Gilead Sciences
    May 2024 - Aug 2024 (4 months)
    • Analyzed clinical study, site activity, milestone, and operations data with Python, SQL, Pandas, and Snowflake to uncover delay patterns that supported faster trial review discussions.
    • Engineered ML-ready features from enrollment, visit, site, and milestone records using Pandas, NumPy, and feature engineering, increasing dataset readiness by 27%.
    • Trained Scikit-learn regression and classification models with cross-validation on clinical operations data to estimate milestone delay risk and guide earlier study follow-up planning.
    • Validated source-to-Snowflake datasets through SQL, dbt, data validation, and reconciliation checks, cutting reporting defects by 30% before clinical dashboard refresh cycles.
    • Profiled m
  • Cognizant
    Data Engineer
    Cognizant
    Jan 2022 - Jan 2023 (1 year 1 month)
    • Developed Python and SQL ETL pipelines for customer, transaction, and operations data, giving enterprise BI teams cleaner Snowflake inputs for recurring client reports.
    • Structured Snowflake warehouse tables with SQL, dimensional modeling, and data warehousing logic to keep customer and transaction history consistent across reporting cycles.
    • Automated record-count, null, duplicate, and file completeness checks using Python, SQL, and reconciliation checks, cutting manual validation effort by 22%.
    • Tuned SQL joins, filters, and aggregation logic across large reporting datasets, shortening dashboard refresh cycles by 18% during monthly business reviews.
    • Standardized raw enterprise files from AWS S3 with Pandas, NumP
Education verified_user 0% verified
  • University of North Texas
    Master of Advanced Data Analytics
    University of North Texas
    Aug 2023 - May 2025 (1 year 10 months)