Data Scientist Senior

Llewelyn Allotey

612-***-**** ********.*******@*****.*** 3317 Emerson Ave S, 55408

SKILLS

ML: XGBoost, Logistic Regression, Linear Regression, K-nearest Neighbors, Random Forest, Gensim, BERT, TensorFlow, NLP, Recommender Systems, Time Series, Survival Analysis, Prophet, Pytorch,Keras Big Data: Apache Hadoop, Apache Spark, Apache HIVE, Apache Sqoop, MapReduce, Pyspark, Pandas, Sci-Kit Learn, Numpy, Databricks, Matplotlib, Snowflake, AzureML, AzureMonitor, Streamlit, Plotly, Dask Programming Languages: Python, Java, C, SQL, R, Scala, Unix Shell, Rust, JavaScript, HTML/CSS Dev Ops: Kubernetes, Jenkins, Elastic Search, Vagrant, Ansible, Chef, Github, Docker, Airflow, DataDog WORK EXPERIENCE

C.H.Robinson Eden Prairie, MN

Senior Data Scientist March 2022 - March 2025

● Developed and deployed ranking models to optimize search results based on user characteristics and web activity, improving user load recommendations.

● Conducted A/B statistical tests and causal inference analyses on proposed features to improve model performance, leveraging optimized SQL, Snowflake, and pandas to pull and process data, and using Jupyter Notebook visualizations to analyze model predictions, track leading indicators, and propose business-tailored actionable improvements to technical and non-technical audiences.

● Built and optimized a recommender system that matched users with available shipping loads using collaborative filtering and cosine similarity techniques.

● Implemented and tracked core metrics to monitor production model performance, using Streamlit dashboards to surface insights and identify optimization opportunities.

● Designed dynamic price optimization models to support real-time pricing, using time series models (Prophet, LightGBM).

UnitedHealth Group - R&D Eden Prairie, MN

Data Scientist January 2018 - March 2022

● Created a generalized ML library and CI/CD pipeline to automate data cleaning, validation, feature selection, and model training on Electronic Health Record( EHR) and medical claims data, leveraging PySpark for data transformations, AzureML jobs API for pipeline orchestration, and MLFlow for experiment tracking.

● Trained Extreme Gradient Boosted Tree (XGBoost) multi-classification and Recurrent Neural Network (RNN) models targeting propensity scores to predict recommended levels of care for post-acute care patients.

● Utilized Azure ML for scalable model training, inference, logging, monitoring, and alerting in disease prediction, hospital admission, and readmission models.

● Created and delivered visualizations outlining business needs, model solutions, and performance insights, enabling data-driven decisions for technical and non-technical audiences. CERTIFICATIONS

Natural Language Processing with DeepLearning.AI – Coursera February 2025 Certificate: https://coursera.org/verify/specialization/H26WCMCC250B EDUCATION

University of Minnesota - Twin Cities Minneapolis, MN College of Continuing & Professional Studies September 2013 - May 2017

● B.A in Information Technology Infrastructure

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