Jerry Yu

addsau@r.postjobfree.com • 857-***-****

*** **** *****, ******, ** 92618

linkedin.com/in/jerryytp • github.com/mr-jree

SKILLS

Computer Languages: Python, SQL, Tableau

Languages: Mandarin (fluent), English (fluent)

Tools: AWS SageMaker, pandas, scikit-learn, matplotlib, numpy, XGBoost, seaborn Techniques: supervised and unsupervised machine learning, natural language processing (NLP), cost-benefit analysis

EXPERIENCE

Data Scientist Intern, Fresenius Medical Care North America, Waltham, MA July 2019 – January 2020

• Led Fresenius’s implementation of AWS SageMaker -the company’s first live-prediction model hosted in the cloud, evaluated potential impact, and supported operationalization of the model.

• Developed and conducted ad-hoc analyses and deep dives using Python, SQL, and Tableau to facilitate decision making for various levels of management.

• Trained multiple classification models (logistic, decision tree, and XGBoost) & NLP models to improve care of 180,000 dialysis patients with kidney failure.

• Summarized complex project findings and recommendations to C-suite executives, data scientists, and data analysts to improve model-based workflows.

• Designed, documented, and maintained model specifications and operational details.

• Cleaned and aggregated multiple EMR data sources (e.g., treatment vitals, monthly lab works, and free-text clinical notes) in Python.

• Collaborated with data analysts and IT specialists to optimize data readability in AWS S3, model prediction, and delivery speed.

• Created Tableau dashboard to track actionable metrics of nurse intervention. Data Scientist Consultant, Viacom, Boston, MA April 2019 – July 2019

• Performed attribution and cluster analysis on the client’s CPM funnel using K-prototype to create eight segments for demographic targeting and made recommended solutions to optimize views for each demographic.

• Optimized Viacom’s conversion funnels using Python and Tableau that yielded a 5% increase to profit margin by providing demographic targeting on digital and social channels.

• Established user-interactive Tableau dashboards for KPIs along conversion funnel across different channels to help optimize CPC.

• Predicted future CPM using XGBoost with an AUC of 0.87 to compare the effectiveness of paid ads traffic with organic traffic, and provided actionable insights to the marketing team.

• Used random search and genetic programming to optimize XGBoost and ExtraTrees classification hyperparameters using dask and tpot.

Sales Analyst, Yesware, Boston, MA August 2017 – August 2018

• Produced analytics dashboards for high MRR customers with Mode Analytics.

• Queried data with SQL from Redshift, transform data with Python for business analyses and blog posts (emails sent, email replay rates, and call connect rates by rep by industry per day.)

• Cleaned data as they are being prepared to be transferred to Snowflake; ensure integrity of database and data warehouses.

EDUCATION

MS Data Modelling Northeastern University 2020

BS Business Adm & Econ Northeastern University 2017

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