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Sample resume · 10 years · senior individual contributor
Senior Data Scientist resume sample
Applied ML, experimentation and production models, written for lead and senior data science roles.
Fictional demo resume. The name Harish Kashaboina is used for illustration only. Employers, colleges (other than any named school or university), projects, dates and numbers are made up to show the format. This is not a real person's career, and the contact email is a placeholder.
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HARISH KASHABOINA Senior Data Scientist · Applied ML & Experimentation harish.demo@example.com | Hyderabad, Telangana SUMMARY Senior data scientist with 10 years of turning business questions into models that teams actually use: demand forecasting, churn and pricing. Strong in Python, SQL and experiment design, and comfortable taking a model from notebook to monitored production service with engineering. Known for explaining trade-offs plainly to business leaders and for mentoring junior data scientists. EXPERIENCE Senior Data Scientist, Northwind Commerce, Hyderabad Apr 2021 – Present - Lead data scientist for demand forecasting across 3,000+ products; replaced spreadsheet forecasts with gradient-boosted models that cut stock-outs by 18% - Designed the company's experimentation guidelines (power analysis, guardrail metrics, sequential testing) now used by 5 product teams - Partnered with ML engineers to ship models as versioned services with MLflow, feature checks and drift alerts - Built a churn-risk model and a simple reason-code layer so retention teams could act on each score, not just read it - Mentor 3 data scientists through weekly reviews of modelling choices and evaluation Data Scientist, Kestrel Analytics, Bengaluru Jun 2018 – Mar 2021 - Built price-elasticity models for a retail client, giving category managers a what-if tool for discount decisions - Engineered features from clickstream and order data in PySpark, cutting model training time from 6 hours to 40 minutes - Presented model results and limits to client leadership in monthly reviews, turning findings into 2 pricing pilots Analyst, Data Science, Bluefin Insurance Services, Hyderabad Jul 2015 – May 2018 - Developed claim-fraud scoring with logistic regression and random forests, prioritising investigator queues - Automated weekly portfolio reports in Python and SQL, freeing about a day of analyst time each week PROJECTS Forecast evaluation toolkit Internal Python library for backtesting forecasting models - Standardised rolling-origin backtests and error metrics so teams compare models the same way Tech: Python, pandas, statsmodels Uplift modelling for retention offers Targeting offers at customers whose behaviour the offer is likely to change - Compared two-model and meta-learner approaches; chose the simpler model after showing similar uplift Tech: scikit-learn, causal ML EDUCATION M.Tech, Computer Science Lakeview Institute of Technology | Hyderabad | 2015 SKILLS Languages & data: Python, SQL, PySpark, pandas Machine learning: scikit-learn, XGBoost, LightGBM, time-series forecasting, causal inference Experimentation: A/B test design, power analysis, Bayesian methods MLOps: MLflow, Docker, Airflow, model monitoring LANGUAGES English – Professional, Telugu – Native, Hindi – Fluent