Machine Learning Scientist

SAIRAM D RAYAPROLU

Machine Learning Scientist Coppell, TX 75019 313-***-****

Visa Status: H-1B with EAD (Can work immediately with EAD) *********@*****.*** linkedin.com/in/sairamray

Driving Product Impact Through Advanced Analytics

Machine Learning Scientist with a track record of delivering high-impact predictive models in insurance, retail, and hospitality. Adept at transforming complex data into actionable insights that drive revenue and business decisions.

CROSS FUNCTIONAL COMPETENCIES

• Business problem conceptualization

• Product and user analytics

• Metric design and visualization

• Mentoring and talent development

• Presentation to CXOs and executives

• Bridging product, data and model

• Hypothesis testing and inference

• Performance estimation and validation

• Model explanation and interpretation

• Feature importance and causality

EDUCATION

Doctor of Philosophy (PhD), Statistics, UNIVERSITY OF CONNECTICUT Master of Science (MS), Applied Mathematics, UNIVERSITY OF ARIZONA Bachelor of Technology (BTech), Chemical Engineering, INDIAN INSTITUTE OF TECHNOLOGY CERTIFICATIONS

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning - DeepLearning.AI Fundamentals of Generative AI - Microsoft

What is Generative AI - LinkedIn, Agents and Agentforce Basics - Salesforce RESEARCH

Rayaprolu S., Chi Z. False Discovery Variance reduction in Large Scale Simultaneous Hypothesis Tests, Methodology and Computing in Applied Probability. (2020) Subject Areas: Bayesian multiple testing, largescale inference, stochastic modeling, simulation PROFESSIONAL EXPERIENCE

VENTIV TECHNOLOGY 08/2021 – 06/2024

Advanced Analytics Lead, Workers Comp Insurance Claims Analytics Atlanta, GA

• Spearheaded machine learning modeling for a startup team for Ventiv’s workers comp claims risk management of a major hospitality company. Led to ROI of $10M.

• Orchestrated stakeholder collaboration to identify high impact use cases and define ML product strategy.

• Designed and built three predictive models for worker compensation claims product leading to their deployment in three different industry domains.

• Delivered presentations on product performance and insights to the CEO, facilitating data-driven decision-making.

• Cultivated high-performing data science team, overseeing recruitment, mentoring, and fostering model ownership.

SAIRAM RAYAPROLU Page 2

CITIZENS BANK 08/2020 – 05/2021

ETL Lead, Lending-Risk Model Data Coppell, TX

• Architected SQL scripts to extract data from data warehouse for lending risk predictive models. Collaborated with product and modeling teams to implement robust ETL processes. BLUE YONDER 04/2019 – 06/2020

Demand Forecast Consultant, Retail Demand Forecasting Coppell, TX

• Diagnosed and resolved demand forecast issues at item level for a major grocery chain resulting in accuracy improvements of 50%. Explained ML driven forecasts to non-technical users. PLYMOUTH ROCK ASSURANCE 01/2017 – 03/2019

Sr. Decision Scientist, Auto Insurance Loss Modeling and Pricing Boston, MA

• Computed automobile insurance rates based on loss, consumer segments, and regulations. Developed GLM models for MA auto insurance, impacting revenue more than $200M. WALT DISNEY PARKS AND RESORTS 09/2013 – 01/2017

Decision Science Consultant, Hospitality Product Forecast Validation Orlando, FL

• Validated demand forecasts for Disney's Orlando resorts, influencing revenue over $400M.

• Innovated metrics to analyze forecast patterns, extracting critical insights for revenue. management team.

• Led data-driven insights that resulted in a projected $10M annual ROI and a $4M product purchase.

TECHNICAL PROFICIENCIES

• Data analysis: Exploratory data analysis, data quality, model choice

• Statistical inference: Hypothesis (A/B) testing, sample size, p-values, simulation

• Statistical Modeling: GLMs, logistic regression, time series, survival models, Bayesian methods

• Decision Science: Forecasting, time series, segmentation, risk modeling, ensemble learning

• User Analytics: Causal analysis, feature importance, large scale testing, UX

• Model management: data pipelines, feature selection, validation, documentation

• Collaboration with Product: Product requirements, metrics, data analysis, compliance

• Collaboration with Data Engineering: data drift, code productizing, scaling, monitoring

• High-level languages: Python (pandas, scikit-learn, NumPy, and statsmodels), R

• ETL: SQL for database querying, SAS

• Statistical programming: SAS, R, MATLAB

• Data visualization: Tableau

• Supervised ML techniques: regression, classification, feature influence

• Unsupervised ML techniques: clustering, dimension reduction

• Learning algorithms: (e.g., decision-trees, random forests, boosting, (xgboost) K-means)

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