FA AKHSH
Warren,MI
Summary
Senior AI/ML Scientist with a Ph.D. in Operations Research and a proven record of designing and deploying production-grade forecasting, simulation, and generative AI systems. Specializes in transforming ambiguous, high-impact questions into end-to-end analytical products that support strategic planning, early issue detection, and engineering decision support. Recognized for technical depth, clear communication, and strong ownership across the full lifecycle—problem framing, architecture, modeling, evaluation, deployment, and continuous improvement. Multiple solutions have been awarded GM Trade Secret (TMS) status.
Overview
6
6
years of professional experience
Work History
Senior Project Manager (Operations Research & Data Scientist)
GENPACT
01.2021
- Led operations research and advanced analytics initiatives for Smith & Nephew, focusing on supply chain and Rough-Cut Capacity Planning (RCCP).
- Applied process mining and statistical modeling to diagnose bottlenecks and quantify improvement opportunities across planning workflows.
- Designed automated data pipelines, curated analytical data models, and executive-level Power BI dashboards, significantly improving transparency and speed to insight for multiple business units.
Senior Scientist (AI/ML)
GENERAL MOTORS
Warren, MI
01.2022 - Current
- Lead AI/ML initiatives that underpin enterprise decision-making, from demand forecasting and simulation to generative-AI-based engineering tools and anomaly detection. Responsible for technical direction, architecture, and delivery across multiple high-impact products.
- Moonshot – Market Demand Simulation & BEV Share Forecasting
- Translated high-level strategic questions into a robust, production-ready BEV share forecasting system used by planning and strategy teams.
- Re-engineered core statistical components and scenario logic, improving forecast accuracy, robustness, and long-term maintainability.
- Embedded the tool into scenario planning workflows, informing capacity, investment, and portfolio decisions under uncertainty.
- Achieved GM Trade Secret (TMS) designation for model architecture and innovation.
- "Have We Seen It Before?" – Generative AI for PRTS / GIMS / Warranty
- Served as technical lead and architect for a contextual RAG-based LLM solution that surfaces relevant historical cases, documents, and issues from PRTS, GIMS, and Warranty data.
- Designed the retrieval pipeline, document processing, and evaluation strategy, with emphasis on relevance, reliability, and user trust for engineering stakeholders.
- Reduced manual search and investigation effort by surfacing context-aware, high-value insights from large heterogeneous corpora.
- Solution awarded TMS status, enabling secure production deployment and broad enterprise adoption.
- Early Launch Issue Detection (DTC) – Pre-SORP
- Led the development of an AI-enabled early fault detection system identifying co-occurring DTC patterns using unsupervised techniques (including FP-Growth).
- Built modular ML pipelines, scalable infrastructure, and integrated dashboards for real-time diagnosis and triage.
- Enabled earlier identification and prioritization of potential launch issues, contributing to reduced warranty risk and faster diagnostics.
- Recognized with TMS designation for the underlying modeling and system design.
- Survey Respondent Anomaly & Fraud Detection
- Designed an ML-based anomaly and fraud detection framework to flag low-quality and fraudulent survey respondents.
- Improved classification precision, operational efficiency, and downstream analytics quality for Global Planning & Customer Research.
- Earned TMS protection for the approach and implementation, supporting enterprise-wide use.
Senior Operations Research Analyst
UPS
01.2020 - 01.2021
- Developed and deployed optimization and heuristic models for dispatching and logistics operations, aligning model design with service levels and operational realities.
- Leveraged statistical analysis, clustering, and text mining to refine algorithms and improve routing, dispatch performance, and resource utilization.
- Owned the end-to-end ML lifecycle in Python, from data preparation and feature engineering to validation and production-aligned integration with engineering and operations teams.
Education
Ph.D. - Operations Research
Southern Methodist University
01-2019
M.S. - Mechanical Engineering
University of Nebraska – Lincoln
01-2015
M.S. - Industrial Engineering
University of Nebraska – Lincoln
01-2012
Skills
- AI & Data Science
- Supervised & unsupervised learning
- Predictive modeling & clustering
- Anomaly & fraud detection
- Time-series & forecasting
- Generative AI & LLMs
- Contextual RAG system design
- Prompt design & evaluation
- Engineering decision-support tools
- Knowledge retrieval applications
- Optimization & OR
- Network & capacity optimization
- Heuristics & approximation methods
- Simulation & scenario modeling
- Operations strategy & planning
- Platforms & Tools
- Python (pandas, NumPy, scikit-learn, PySpark)
- SQL, Databricks, distributed data processing
- Git/GitHub, Power BI, advanced Excel
- Dashboarding & reporting for executives
- Languages & Libraries: Python (pandas, NumPy, scikit-learn, PySpark), SQL
- Data & Compute Platforms: Databricks, distributed data processing environments
- ML & Analytics: classification, regression, clustering, anomaly detection, forecasting, simulation
- OR & Optimization: network optimization, capacity planning, heuristics and meta-heuristics
- MLOps & Collaboration: Git/GitHub, reproducible workflows, documentation and knowledge sharing
- Visualization & Reporting: Power BI, advanced Excel, bespoke dashboards for technical and executive audiences
Accomplishments
developed several products for different and vast veriaty team customer ...
LEADERSHIP & COLLABORATION
- Act as technical lead on cross-functional teams, aligning engineering, operations, strategy, and quality around shared objectives and success metrics.
- Known for clear, structured communication that translates complex model behavior and uncertainty into actionable insights for decision-makers.
- Provide mentorship and guidance on modeling choices, experimentation practices, and responsible deployment of AI/ML systems.
- Consistently recognized for high ownership, follow-through, and the ability to shepherd initiatives from initial concept through sustained production adoption.
Timeline
Senior Scientist (AI/ML)
GENERAL MOTORS
01.2022 - Current
Senior Project Manager (Operations Research & Data Scientist)
GENPACT
01.2021
Senior Operations Research Analyst
UPS
01.2020 - 01.2021
M.S. - Mechanical Engineering
University of Nebraska – Lincoln
M.S. - Industrial Engineering
University of Nebraska – Lincoln
Ph.D. - Operations Research
Southern Methodist University