Principal Data Scientist Resume Newark, CA - Hire IT People

SUMMARY

Experience: 5+ years unsupervised machine learning, data mining, and big data research. 5+ years in economic analysis and large scale data analytics.

TECHNICAL SKILLS

Programming Languages: R, Python, SAS, SQL, MATLAB, STATA, C, Shell

Computing Framework: Hadoop/ MapReduce

Operating Systems: Windows, IOS, Linus, Microsoft Series, Latex, Adobe Illustrator

PROFESSIONAL EXPERIENCE

Confidential

Principal Data Scientist

Responsibilities:

Initiated and planned the scope of data scientist work in the company with co - Founders.
Designed and developed algorithm end-to-end to support the business needs, such as built predictive model based on eye-movement video to predict the probability for various diseases.

Confidential, Newark, CA

Ph.D. Research Intern

Responsibilities:

Proposed a bootstrapping algorithm in R to measure the standard error of property damages estimation through limited sample size.
Researched and developed an innovative modeling algorithm to quantify insurance risk in R.
Designed, tested, and implemented algorithm into the Confidential Assessment Product for the finance team to accurately and efficiently create premiums.
Re-wrote the existing algorithm that quantifies property damages of 10GB+ of data.
Reduced computing time significantly and yielded costs savings of 75%.
Drove valuable insights for the Vulnerability Team that reflect the latest data regarding disasters and risk.
Insights were featured in various Confidential models.

Researcher

Confidential, Davis, CA

Responsibilities:

Proposed a novel data-driven protocol to understand the Malbec wines structure in terms of biochemical and sensory features: (1) Identified synergistic features as variable selection for classifying wines with 20% improvement. (2) Organized a collection of knowledge loci and further for prediction.