Apple

I lead the data science and engineering team at Apple Services Finance. The team focuses on translating business problems and requirements into data products using advanced statistical and machine learning models to support and help Apple leadership make data-driven decisions.

Senior Manager - Data Science and Engineering 

Managing a data science team focusing on cost optimization on Apple infrastructures with the use of statistical analysis and machine learning models.

Data Science Manager

Senior Data Scientist

Ernst & Young

Predictive analysis, time series models, forecasting and machine learning

Data Scientist

University of Michigan Law School

Data Analyst supporting the Empirical Legal Studies Center
Prediction Models, Regression Analysis and Data Visualization using R, JMP and Stata.

University of Michigan

Data Manipulation & Cleansing of a large database (India Census) using Stata and R
GIS Analysis with R
Data Visualization

Data Analyst

Senior Manager - Data Science and Engineering at Apple

I lead the data science and engineering team at Apple Finance - Services and Infra. The team focuses on translating business problems and requirements into data products using advanced statistical and machine learning models to support and help Apple leadership make data-driven decisions.

I am also an open-source contributor and the author of Hands-On Time Series Analysis with R (Packt publication) and several R packages for time series analysis and machine learning applications. Currently working on my next book, Applied Time Series Analysis and Forecasting, which focuses on forecasting at scale. 

Also available on:
Github: https://github.com/RamiKrispin
Medium: https://medium.com/@rami.krispin
Mastodon: https://mstdn.social/@ramikrispin

Rami Krispin

Microsoft

- Drive product strategies and growth for Office apps via product analytics, Causal Analysis, experimentation, developing ML algorithms with focus on Copilot usage, user growth, engagement, and retention. 
- Collaborate with Office Product Managers, Engineers, User Experience researchers, designers and execute cross-functional projects. 
- Provide analytical insights and strategies (growth, engagement, retention and LTV) for the Microsoft Office products.
- Apply Economic theory and practices.
- Reviewer of Machine Learning and Data Science (MLADS) conference and Microsoft Journal of Applied Research (MJAR) journal (internal Microsoft conference and journal).

Sr Data & Applied Scientist Lead

Boeing

• Built machine learning anomaly detection models in Python, identifying aircraft component defects in sensor data, reducing cost and down-time. 
• Developed methodology for forecasting time-series data with intermittent demand of airplane parts (revenue and demand)
• Created an automated cost estimation tool with Machine Learning algorithms for pricing airplane parts.
• Built a causal impact estimation application to measure campaign initiatives and contract performance.

Senior Data Scientist Lead, Digital Solutions & Analytics

T-Mobile

•	Conduct research and analyze large datasets to provide strategic business insights and recommendations for Customer Service.
•	Perform statistical and other quantitative and qualitative analyses utilizing tools and applications including SAS, R, SQL, statistical modeling, and regression analysis.
•	Assist with ad hoc analytical projects, including economic impact assessment, quantitative and qualitative analytics, sensitivity analysis and statistical modeling.
• Notable Projects: Frequent callers analysis and strategic insights; impact assessment of new software tools on call center reps performance and T-Mobile customers behavior and satisfaction through A/B testing and causal inference approaches; Accuracy measurement of call reasons after AI implementation; impact assessment of HR policy adjustment on call center reps performance and T-Mobile customers behavior and satisfaction.

Data Scientist, Customer Service Analytics

Washington State University

•	Completed PhD program in Economics and graduate minor in Statistics at Washington State University.
•	Teaching Experience: Instructor, "Business Management Economics" course, Spring 2012; Teaching Assistant, "Economics Capstone" course, Fall 2011.

Scientific Researcher

UNDP

Intern

Tashkent Institute of Irrigation and Melioration

Teaching practical classes for "Environmental and Natural Resource Economics" and "Economic Methods for Decision-Making" courses

Research Teaching Associate

Experienced Data Scientist with a 18+ years of experience working in academia, IT, aerospace, telecommunication and agricultural industries. Skilled in Causal Inference, Machine Learning, Deep Learning, Artificial Intelligence (AI), Econometrical and Statistical Modeling, Economics and Optimization. Strong programming skills in R, Python, SQL. Great communication skills.

Last Updated: 05/21/2024

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Rami Krispin

Andrey Zaikin, Ph.D.

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