SUMMARY

• 14 years of applying machine learning, data mining, and predictive modelling in Marketing Database Analysis (CRM), Banking (Fraud, ERM), Oil & Gas, and Public Services (resources optimization)
• Experience of effective coding in SAS (12 years), R (4 years), Python (1 year), TensorFlow 3 years of application of SAS Big Data technology (in - memory data visualization and analytics, Hadoop) Managed 3 projects with the total budget of $240,000 with 2-5 consultants on time and on budget 2 years of applying Agile to development and timely delivery of the software solutions Developed and successfully delivered technical presentations to groups of 6-40 experts Passed 2 actuarial exams Probability and Financial Mathematics Looking for a Data Scientist, Statistical Consultant position.

TECHNICAL SKILLS

• R
• Python
• SAS
• SQL
• Azure ML
• Hive
• Latin Pig
• Spark
• SPSS
• MatLab

PROFESSIONAL EXPERIENCE

Confidential, San Jose

Data Scientist

Responsibilities:

• Responsible for analysis of data patterns, designing prototypes, and implementing predictive and machine learning solutions that leverage large datasets using a wide range of analytical tools, methods, and platforms (Python, R, Hadoop)

Data Scientist

Statistical Consultant

Responsibilities:

• Deliver customers segmentation, data mining and optimization of the marketing campaigns by applying Random Forest, De­cision Tree, and Neural Network modelling with R, Python, MS Power BI, and SAS
• Applied advanced ETL and exploratory analysis to discover patterns in users’ log-ins to the sales web-site
• Developed a design of an A/B marketing experiment intended to boost the sales in the cab services
• Trained and tested decision tree models for predicting sales forecast overrides and interpreted the findings to the business
• Developed Decision Tree models for predicting client churn in 3 markets and suggested policy changes to retain the cus­tomers
• Provided reports with interpretation of the results, recommendations on the models’ application and further enhancement.

Confidential

Technical Consultant

Responsibilities:

• Developed predictive models for optimization of SAGD oil extraction using Neural Network and Bayesian modelling
• Was an active member of SAS Bookrunner development team using Scrum and Agile methodologies for 2 years
• Implemented cluster analysis for grouping gas wells by their location, geology, and production profile
• Applied hierarchical time series models to predict production volume in multi-level 2bn MMBTU gas transportation system for 30-year horizon
• Developed an analytical model for optimization oil production and storage using a non-linear algorithm
• Developed QA models for quantitative validation of risk metrics (Potential Future Exposure, Value-at-Risk, Cash-Flow-at- Risk) and averaging price functions for oil, gas, and electricity contracts and their derivatives; the software features were delivered to the customers and received positive feedback
• Managed 3 projects to the total of $120,000 with 2-5 consultants on time and on budget
• Lead development of 3 custom BI reporting applications in Oil & Gas and in Public Services to enhance data visualization and facilitate decision making
• Developed and successfully delivered a training course, technical presentations and demos to groups of 6-40 experts.

Confidential

Quantitative analyst - Stress Testing, Credit Portfolio Information Manager

Responsibilities:

• Applied time series models to predict and stress test delinquency rates (PD) and losses given default (LGD), and Exposure- at- Default (EAD) with respect to macro-economic factors in 60-month horizon in compliance with Basel II requirement
• Developed a spatial diagnostic model for monitoring delinquency rates in the mortgage portfolios and presented it at ERM symposium and at Midwest SAS user group meeting
• Regularly reported on loan-to-value analysis for the mortgage portfolios and performance analysis for the credit card portfo­lios that included volumes, credit quality, utilization, delinquency, and attrition rates.

Confidential, Kansas City

Sr. Research Analyst

Responsibilities:

• Developed methodology for selecting best hospitals in 6 specialties by their performance in a set of non-normally distributed indicators with adjustment for the patients’ acuity
• Applied generalized mixed models with repeated measurements and Binomial, Negative Binomial and Poisson distributions in modelling effects of quantity and quality of staffing on negative patients’ outcomes, suggested policy changes based on the models’ findings
• Developed reliability analysis with application of ANOVA and Bayesian regressions
• Contributed with advanced statistical analysis into 2 papers published in the leading research journals

Confidential, Kansas-City

Corporate Analyst Intern

Responsibilities:

• Developed decision tree models for customers’ segmentation and predictive models for their retention, presented the results to the panel of 26 experts
• Motivated a transfer from the conventional market segmentation by the clients’ tenure to the segmentation by the income with higher economic homogeneity and better model fit of the data.

Confidential, Ames, Iowa

Teaching and Research Assistant

Responsibilities:

• Analyzed option prices on most frequently traded futures and found evidence of statistically significant profits for the option writers in the degree paper
• Received Dean’s Excellence Award for managing 24-30 assistants at the ISU Economics Help Lab
• Collected data, developed statistical model for research project "Economic development of rural areas in the US Midwest"
• Developed statistical analysis for 8 research projects and received positive feedbacks on the work done
• Taught 3 Introductory and Intermediate level Statistics classes with near 40 students in each.