Data Scientist Machine Learning
Resume:
FARZAD YOUSEFI, PHD
San Francisco Bay Area 628-***-**** *************@*****.***
Summary
Accomplished data scientist with 7+ years of experience and a proven history of successful collaboration with cross-functional teams. Proficient in statistics, machine learning, and data-driven storytelling, with a keen focus on optimizing ROI and providing integral support for product development and commercialization initiatives.
Skills
Natural language processing
Experimental design
Dimensionality reduction
Optimization techniques
Deep learning
SQL databases
Python programming
Machine learning algorithms
Statistical modeling
A/B testing
Experience
Freelance Data Scientist Apr 2023 to Current
Self Employed
Developed and maintained predictive models to identify customer segments for targeted marketing campaigns.
Followed industry innovations and emerging trends through scientific articles, conference papers or self-directed research.
Deployed predictive analytics systems for real-time decision making. Collaborated with stakeholders to define requirements for new AI products or services. Senior Data Scientist Oct 2021 to Mar 2023
LifeScan
Designed and implemented a Marketing Mix Modeling solution in partnership with the marketing department.
Processed and unified over 25 sales and engagement data sources. Developed linear regression and Random Forest models to identify influential marketing channels. Created an unsupervised machine learning solution to cluster health care providers (HCPs) for targeting objectives.
Built a hierarchical clustering model with 50+ features to successfully categorize approximately 600,000 HCPs into homogeneous groups.
Transferred finalized prototype to market research team after successful refinements. Improved the performance of the customer churn prediction model. Constructed and refined XGBoost classification model, achieving superior performance compared to the existing production model.
Redesigned churn metrics to align with revised business strategies. Data Scientist Jul 2020 to Sep 2021
Alameda Behavioral Health Care Group
Engineered Random Forest classification models for identifying individuals vulnerable to mental health conditions.
Executed causal inference analyses to determine underlying factors influencing personality disorders among underprivileged Alameda County populations.
Machine learning/Artificial Intelligence specialist Nov 2018 to Nov 2019 Alcimed Princeton, NJ
Directed execution of customized data analysis initiatives for pharma industry partners. Examined novel data analysis techniques aligned with healthcare and pharma sector needs. Formulated sale-peak prediction tools tailored for multiple market conditions, benefiting client product groups.
Postdoctoral Fellow Sep 2017 to Nov 2018
University of Pennsylvania Philadelphia, PA
Conducted Cluster analysis of infrared imaging spectra of genetically modified mice disc sections Developed a multiple linear regression model to predict NMR-derived results Developed a multivariate partial least square model based on NIR spectral input to predict the moduli of the constructs
Designed and conducted A/B tests for secondary screening of 'hits' Studied progression of gene expression changes following mechanical injuries to native and engineered cartilage
Education
PhD, Bioengineering Aug 2017
Temple University
Certificates
Neural Networks and Deep Learning, Coursera, AXLCN779MEDB Structuring Machine Learning Projects, Coursera, UA5HS8BGAB87 Convolutional Neural Networks, Coursera, 6KZZAMM4CYJP Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization, Coursera, RLSTY5B2Q7S9
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