The Discrete Laplacian

Resume

Sharat Chandra

Data Scientist

Senior Data Scientist with 6+ years experience building and interpreting complex predictive data models, open to Data Science, Software Engineering, and Privacy/T&S roles

Experience

Ford Motor Company

Dearborn, MI (Remote)

Senior Data Scientist - Privacy Engineering Tech Lead

Jul 2023 - Present

  • Leads Privacy Enhancing Technologies (PET) products & research workstream as tech lead, mentoring 2 data scientist direct reports and developing 5-year PET strategic vision
  • Works with Legal to establish data purpose, consent, and compliance criteria for products across the org and recommends appropriate engineering solutions
  • Prevented over $10M in total legal & remediation costs by identifying, quantifying, and supporting mitigation of fraudulent vehicle activity both in the US and EU leading to violation of privacy regulation
  • Architected and developed streaming-at-scale, enterprise level differential privacy data product to reduce data purpose and retention legal burdens, aligning many cross-functional stakeholders
  • Developed 15+ POCs and tailored privacy solutions for Business, Product, and ML Engineering teams
  • Developed 3+ solutions to enable privacy-preserving marketing, behavior analysis, and 3rd party data share business use cases using cryptographic techniques, differential privacy, and k-anonymity
  • Designed and implemented empirical reidentification risk metrics including membership inference attack metrics and LiRA
  • Represented Ford at Eyes Off Data Summit (speaker), OpenDP Conference (speaker), TPDP Conference, and Privacy Enhancing Technology Summit, and created privacy educational material for Ford and Ford legal

TikTok

San Francisco, CA

Data Scientist - Risk Data Mining (as Lead Data Scientist)

Dec 2021 - Feb 2023

  • Lead the security effort under the US Data Security (USDS) - Platform and Content Integrity group for the TikTok LIVE product and took ownership of the US region LIVE security domain
  • Built rules and deployed 8+ daily retrained machine learning models currently running on live TikTok data to mitigate business risks in the LIVE streaming domain
  • Prevented over $1.2M in losses to fraudulent transaction activity by underground industry groups over the course of 4 months
  • Mitigated Anti-Automation attacks, API abuses, Underground Industry exploitation of data integrity, erotic redirection attacks, audience harvesting attacks, and gambling promotions
  • Worked on both mobile and web platforms within the US data centers and addressed cross-region impacts due to US fraud sources
  • Defined risk control measurements. Quantified, generalized, and monitored risk related business and operational metrics
  • Owned, migrated and maintained US LIVE related data sources, services, and metric dashboards as well as built platform health sharing channels compliant with USDS policy and legal restrictions to inform global teams about the state of the US LIVE streaming
  • Communicated and coordinated collaborations with multiple XFN teams including Data Integrity teams, Trust and Safety, E-Commerce, Agency teams, and Business and Product teams both in the US and the rest of the world across data separation regions and timezones
  • Trained 3 new employees in the USDS Live security domain

Nickerson & Associates, LLC

Seattle, WA

Data Analyst

Nov 2019 - Apr 2021

  • Constructed high fidelity data warehouses of thousands of our client’s employees linking employment histories, tax records, income data, and various other real world sources together to derive insights that would otherwise be extremely difficult to analyze
  • Analyzed over 30 Individual and Class Action lawsuits, using future employment probability and Options Pricing models (eg Black-Scholes or Binomial Models) to quantify damages owed to thousands of plaintiffs across the US
  • Corresponded with legal counsel about client needs and developed detailed data visualizations to convey our findings and methodology to a general audience

NASA Jet Propulsion Laboratory (JPL) + US Army TARDEC

Pasadena, CA

Software Developer (Intern)

Jan 2016 - Aug 2016

  • Prototyped and built the first full pipeline from real-world input GIS terrain data to human-readable data products like Go-No Go maps and Safety/Success maps for semi-autonomous ground vehicle operators supporting the development of the NG-NRMM Pilot Project, in collaboration with the US Army and a NATO initiative
  • Implemented new features in the ROAMS simulation suite (written in Python) to support 4-Wheel ground vehicles, like Humvees, and adapted the existing autonomous driving logic made for rovers to the new Ackermann steering geometry
  • Performed Monte Carlo simulations studying varying levels of driving autonomy and sensor suites and collected data asynchronously from 8 local machines performing 36,000 runs, and much larger batches of runs performed on the Pleiades supercomputer at the Ames Research Center. As of May 17, 2021, this pilot project (in conjunction with the work of 60+ NATO scientists across the globe) has been adopted as a standard by the U.S. Army DEVCOM Ground Vehicle Systems Center

Volunteering

Educational Employees Credit Union

Fresno, CA

Associate Volunteer Board Member

Feb 2025 - Present

  • Attends and participates in board meetings, committee sessions, and strategic planning retreats to understand how the board guides the credit union’s mission, financial soundness, and compliance.
  • Gains knowledge of financial statements, regulatory requirements (e.g., NCUA or provincial regulators), risk management, and credit union principles. Also, I take classes on people management skills and situational leadership
  • Contributes ideas and perspectives to discussions on policy, growth, community engagement, and member services—without holding a formal voting role
  • Serves several board committees to develop deeper insight into specific operational areas
  • Build leaderships and governance experience

Skills

  • Differential Privacy & Cryptography: Prio, HDMM, RAPPOR, MIAs, LiRA, Federated Learning, Local Sensitivity Hashing, Shuffle DP, Central/Local DP, K-Anonymity, TEEs, Clean Rooms, ZKP
  • Data Science: Predictive Analytics, Data Mining, Text Analytics, Big Data Analytics, Data Visualization, Deep Learning, Machine Learning, Optimization, Monte Carlo, Bayesian Models, k-NN Methods, Louvain Clustering, DBSCAN, GBDTs, Random Forests, Linear Classifies, SVM, Kernel Machines
  • Technologies: Hive, Spark, Flink, Presto, Clickhouse, Python, Numpy, Pandas, Scikit-Learn, PyTorch, Seaborn/Matplotlib, SAS, Django, R, SQL, Excel, Tensorflow

Education

Cornell University

Ithaca, NY

Certificate in Machine Learning

Apr 2021 - Sep 2021

University of Washington

Seattle, WA

Master of Science in Mathematics

Aug 2016 - Jan 2019

University of California, Irvine

Irvine, CA

Bachelor of Science in Mathematics

Aug 2012 - Dec 2015