Senior Data Scientist in Statistics & Experimentation

SAM SHARIF

SENIOR DATA SCIENTIST · STATISTICS & EXPERIMENTATION · MACHINE LEARNING

Drexel Hill, PA 267-***-**** *********.**@*****.*** github.com/caffeinatedev SUMMARY

Senior Data Scientist with 8+ years turning complex datasets into decisions across healthcare, finance, retail, and compliance. Strong foundation in statistical modeling, hypothesis testing, A/B experimentation, forecasting, and customer analytics, paired with hands-on machine learning in Python, SQL, scikit-learn, and PyTorch. Experienced building demand-forecasting, segmentation, and NLP systems end-to-end — from exploratory analysis and feature engineering through modeling, evaluation, and stakeholder communication — with growing depth in Generative AI (LLM fine-tuning and RAG). Focused on measurable business impact: better accuracy, lower cost, faster decisions. TECHNICAL SKILLS

Languages Python, R, SQL, MATLAB

Statistics & Experimentation Hypothesis Testing, A/B Testing, Experimental Design, Causal Inference, Regression, Bayesian Methods, Confidence Intervals, Statistical Modeling Machine Learning Scikit-learn, XGBoost, LightGBM, Random Forests, Regression, Classification, Clustering, Recommendation Systems, Feature Engineering, Model Evaluation Forecasting & Time Series Prophet, ARIMA, LSTM, GRU, Temporal Fusion Transformers, Seasonality & Demand Modeling Analytics & Visualization Exploratory Data Analysis, Cohort & Segmentation Analysis, KPI Reporting, Dashboards, Tableau, Power BI, Matplotlib, Seaborn

Data & SQL PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery, Pandas, NumPy, Apache Spark, Airflow, ETL Pipelines

NLP & Generative AI BERT, GPT-4, Sentiment Analysis, Text Classification, Topic Modeling, RAG Pipelines, LangChain, LLM Fine-Tuning (LoRA, QLoRA)

Deep Learning PyTorch, TensorFlow, Keras, CNNs, Computer Vision (YOLO, UNet), Hugging Face Transformers

MLOps & Cloud MLflow, Docker, Kubernetes, CI/CD; AWS (SageMaker, Bedrock, S3), Azure (ML, OpenAI, Cognitive Services), GCP (Vertex AI, BigQuery)

PROFESSIONAL EXPERIENCE

Senior Data Scientist Feb 2021 – Present

FlexTrades

• Built demand-forecasting systems using Prophet, LSTMs, and Temporal Fusion Transformers, improving forecast accuracy by 20% and reducing operational planning error.

• Designed and ran A/B tests and statistical experiments to validate model and product changes, establishing rigorous experimentation and evaluation standards across data science work.

• Applied statistical analysis, feature engineering, and disciplined model evaluation across large-scale datasets, lifting baseline model accuracy by ~15%.

• Delivered predictive-analytics solutions for healthcare and finance clients, translating complex data into decision-ready insights and cutting manual review effort by ~50%.

• Partnered with stakeholders to define KPIs and communicate findings, turning model outputs into concrete business actions.

• Built customer-support automation with NLP summarization and intelligent routing, automating over 65% of routine queries.

• Fine-tuned LLMs (LLaMA, Mistral) with LoRA/QLoRA and built RAG question-answering with Pinecone and Weaviate, reducing inference cost by 40%.

• Developed 3D deep-learning models (UNet3D, VNet) for MRI and CT analysis, improving diagnostic precision by 18%. Data Scientist Mar 2019 – Jan 2021

GameOne

• Analyzed UI and product changes through A/B testing and behavioral analytics, identifying patterns that drove a 15% increase in user retention.

• Developed clustering and customer segmentation models that improved marketing budget allocation, lifting campaign efficiency by ~25%.

• Built time-series forecasting models (LSTM, GRU, TFT) predicting SEC filing volumes, improving capacity planning and preventing deadline-driven overloads.

• Designed NLP workflows with Azure Cognitive Services for sentiment analysis and text classification, reducing manual support handling by 60%.

• Implemented ML-driven lead scoring and segmentation pipelines feeding CRM systems, improving onboarding efficiency by ~30%.

• Fine-tuned YOLOv5 object-detection models for automated visual compliance validation, cutting false positives by ~30%. Data Analyst Mar 2017 – Feb 2019

Verstela

• Wrote and optimized complex SQL across reporting systems, reducing query response times by 60% for high-traffic analytics.

• Built data-driven pricing models and booking logic in Python, lifting conversion by ~20%.

• Developed reporting and analytics on PostgreSQL and Redis-backed systems supporting millions of daily transactions.

• Built automated Python data pipelines and validation for recurring reporting, reducing manual reporting effort by ~40%.

• Integrated third-party data sources (Booking.com, Expedia) with caching and async processing, improving data reliability to 99.5%.

EDUCATION

Master in Information Science • Temple University 2022 CERTIFICATIONS

Microsoft Azure AI Fundamentals • L2 Advanced Proficiency in KNIME • GA Individual Qualification

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