Farrukh Nauman

Principal Consultant | Enterprise Data Platforms · Coding Agents · Time Series ML | PhD

Summary

Principal consultant helping enterprise data teams de-risk platform migrations, cut warehouse cost, and automate analytics workflows with coding agents. I lead and ship in production-scale environments — owning roadmaps, managing stakeholders, and writing code, not slide decks. Selected results:

5–10x faster pipeline with row-level correctness proof after killing a broken optimization.
~1 week from zero to live cross-platform migration validation dashboard.
10-100x faster telemetry classification inference than deep learning baselines for industrial deployment.
Interim team lead for a 4–7 person DS & analytics team at a global industrial manufacturer.

Current focus

Cross-platform migration validation and warehouse modernization in Snowflake / Databricks environments.
Coding-agent workflows for migration, validation, analytics automation, and large code changes.
Time series / telemetry ML for industrial production and edge deployment.
Interim technical leadership: roadmap ownership, stakeholder steering, delivery discipline, and hands-on implementation.
Core stack: Python, SQL, Snowflake, Databricks/Spark, Azure Data Factory, Streamlit, PyTorch, LangChain, OpenAI SDK.

Experience

InertialRange Labs AB

Principal AI Consultant Sep 2025 - | Linköping, Sweden

Engagement: Interim Team Lead – Data Science & Advanced Analytics (Sep 2025 - Present): Client: Global Industrial Manufacturer (Material Handling & Logistics)

Lead a 4–7 person DS/analytics team; own roadmap, stakeholder steering, and technical direction across telemetry analytics, ML, and GenAI automation.
Coordinate transition planning/execution for Databricks → Snowflake while maintaining daily Spark/BI workloads over 23 TB telemetry data.
Built a cross-platform migration validation system using AI coding agents: automated schema comparison, row-count reconciliation, key-distribution checks, and date-range verification across dozens of tables — from zero to live dashboard in ~1 week.
Redesigned a critical daily pipeline from full recompute to validated incremental processing: 5–10x speedup with row-level correctness proof. Killed a faster but fundamentally broken optimization using multi-scale benchmarks and EXCEPT-based validation.
Established in-house direction for machine activity recognition from CAN/telemetry (PoC): privacy-safe labeling workflow, baselines, evaluation harness, and benchmarking vs external PoC (faster inference with comparable accuracy on internal tests).
Prototyped Text-to-SQL workflow automation (PoC): synthetic evaluation dataset generation + instrumentation/logging to analyze failure modes and improve reliability.
Developed a practitioner framework for large code migrations with coding agents: evidence-preservation methodology, behavioral oracles, and AGENTS.md-based quality contracts.
Tech Stack: Snowflake, Azure Databricks, Snowpark, PyTorch, AI Coding Agents (Cortex Code, Codex CLI), LLM Agents (LangChain), Streamlit, Time-Series, Model Monitoring/Serving, Experiment Tracking, Git.

RISE Research Institutes of Sweden AB

AI Researcher & Consultant
Jul 2021 - Aug 2025 | Linköping, Sweden

Led applied AI consulting and project delivery across inspection, edge ML, time series, and industrial automation programs.
Sustainable Fashion AI Automation (2022-2025): Project lead for Vinnova: AI for Circular Fashion and AI lead in CISUTAC, delivering an automated quality-assessment workflow with 40% faster processing and 50%+ reduction in data collection effort via synthetic data.
Low-Energy IoT Solutions (2022): Identified miniROCKET-based time series methods for industrial edge deployment, enabling real-time analysis with roughly 90% lower hardware cost than heavier alternatives.
Established and led an AI mentorship program for Master’s thesis students and supported additional client work in drone edge AI, air-traffic automation planning, traffic analysis, and anomaly detection.

2MNordic IT Consulting AB

Data Scientist & Data Engineer
Dec 2019 - Jun 2021 | Gothenburg, Sweden

Project: Early Warning System for Student Performance (2020: 6 months):

Challenge: Helsingborg school district lacked ability to identify at-risk students early, resulting in up to 40% failure rate in some schools in 9th grade.
Solution: Developed predictive analytics system identifying absence, poor grades in English and Math as the key indicators in 6th grade that predict 9th grade performance, with school-level feature analysis for targeted funding.
Impact: Enabled early intervention for 10% of the student population, and provided data-driven policy recommendations impacting 3,000+ students.
Technologies: Azure DevOps, Azure Functions, Data Factory, Python, SQL, Power BI.

Project: Mathematics Assessment Optimization (2021: 4 months):

Challenge: New digital mathematics test showed inconsistencies with traditional grading schemes, causing confusion and potential inequities.
Solution: Conducted comprehensive data analysis of test results across 8 schools, identifying specific misalignments between grading schemes.
Impact: Findings led to significant improvement in assessment accuracy and informed critical education policy adjustments affecting district-wide mathematics curriculum.
Technologies: Scikit-learn, Statistical Analysis, Python, Data Visualization, Azure Notebooks.

Previous Research Positions

2009–2019

Research Fellow, Chalmers University of Technology: Gothenburg, Sweden (2018–2019) Complex systems modeling, large-scale data analysis
Research Scientist, Niels Bohr Institute: Copenhagen, Denmark (2015–2018) Simulation, forecasting, computational modeling
Research Assistant/PhD Student, Univ. of Rochester: New York, USA (2009–2015) Data analysis, predictive modeling

Education & Certifications

Microsoft Certified

Azure Data Engineer Certificate
2020

University of Rochester

PhD in Physics and Astronomy
Oct 2015 | Rochester, New York (USA)
Focus: Complex Systems Modeling, Data Analysis, Computational Fluid Dynamics, High Performance Computing, C/C++

Awards & Achievements

Horton fellowship from Laboratory for Laser Energetics - full research funding award. 2010-2015
Susumu Okubo Prize for highest performance on graduate comprehensive exam and excellence in coursework. 2011