Data Scientist

Anish Vaidya

St. Louis, MO 979-***-**** ******.*****@*****.***

Experienced in analyzing extensive Geo-Spatial data in the Ag-Tech industry and collaborated with researchers and executives to translate insights into business opportunities. Worked as a self-starter in a dynamic environment. Able to think big with a close attention to detail. SKILLS

• Python

• PySpark

• Machine learning

• Statistics

• Git, GitLab, BitBucket

• AWS

• Windows, Mac OS X, Ubuntu scripting

• SQL

• MATLAB

WORK HISTORY

Data Scientist, The Climate Corporation July 2019 - Present

• Analyzed Geospatial agriculture planter pass data, harvester pass data, planter & harvester equipment data to study grower practices, using Python.

• Worked on complete life-cycle of the Outcome-Based-Pricing model: Worked on defining protocol rules for 2020, develop algorithms, strategy to productionize algorithms, and approve Engineering model for deployment, and model improvements for 2021+.

• Collaborated with Data teams, Product teams, and Engineering teams for the above.

• Performed feature engineering, model selection, and hyperparameter optimization to predict crop yield using Nearest Neighbor Gaussian Process (NNGP) and Linear models.

• Collected data from different sources like AWS S3, Internal Production APIs, etc. to build datasets for algorithms.

• Created large samples of fields to scale OBP algorithms and pilot runs, with Spark SQL.

• Scaled the OBP algorithm to create experimental areas on ~13,200 fields using PySpark on AWS for testing and validation.

• Scaled the OBP algorithm on Latin American fields for Seed Density Projects.

• Optimized Spark pipelines based on memory usage, computational time, and cost.

• Analyzed failures of the OBP algorithm, and created algorithms to detect failures.

• Analyzed and scaled alternate algorithms to improve the performance of OBP models for 2021+.

• Wrote and Reviewed code according to best coding practices. Worked with git version-controlled- systems. Wrote reports on Confluence. Managed tasks with JIRA.

PERSONAL PROJECTS

• Analyzed stock price data with Technical analysis. Developed and tested derivatives trading algorithm using Python. Collected data using Robinhood API. Outperforms S&P 500 by about 5%. EDUCATION

M.S. - Industrial Engineering, Texas A&M University, College Station, TX May 2018 B.E. - Production Engineering, Gujarat Technological University, Gujarat, India May 2014

Contact this candidate