# Principal Forward Deployed Data Scientist - Oil & Gas

**Company:** [Fundamental Research Labs](https://hotfix.jobs/companies/fundamental-research-labs)
**Location:** Houston, TX
**Role:** Solutions Architecture
**Experience:** 7+ years
**Skills:** Python, Docker, FastAPI, Flask, Pyspark, pandas, Xgboost, Lightgbm, PyTorch, AWS, GCP, Azure, Data Engineering, Feature Engineering, Machine Learning
**Posted:** 2026-08-21

> Principal forward-deployed data scientist who deploys and validates machine-learning solutions for Houston-based oil and gas customers, proves business value, and translates customer needs into product improvements. Requires 7+ years of technical experience, advanced statistical expertise, customer-facing experience, and strong production ML skills.

## Job Description

## Responsibilities
- Deploy production use cases with significant business impact and demonstrate definitive ROI.
- Benchmark NEXUS against client baselines such as XGBoost and LightGBM.
- Perform data engineering, feature engineering, preprocessing, model validation, and memory optimization.
- Collaborate with research and product teams to translate operational pain points and data anomalies into product roadmap inputs.
- Identify appropriate business problems, prevent data leakage, and support last-mile integration into VPC, on-premises, and air-gapped environments.
- Manage relationships with IT, C-suite, data science, sales, and solutions architecture stakeholders.
- Explain model predictions and architectural concepts in terms of business value.

## Requirements
- PhD or master's degree in computer science, mathematics, or statistics, or equivalent statistical expertise.
- 7+ years of experience as a technical individual contributor in data science, machine learning, applied science, or ML engineering.
- Experience working directly with customers or business stakeholders in complex enterprise or industrial environments.
- Experience with Docker, orchestration, and performant APIs using FastAPI or Flask.
- Expertise across the end-to-end machine learning pipeline, including problem framing, preprocessing, algorithms, and validation strategies.
- Strong data-handling experience with PySpark and Pandas.
- Demonstrated experience optimizing models for specific business problems.
- Strong communication skills and the ability to translate technical architecture into business value.

## Nice to Have
- PyTorch experience.
- Experience with cloud-native machine learning pipelines on AWS, Google Cloud, or Azure.
- Experience in oil and gas, energy, utilities, industrials, logistics, or heavy-asset environments.
- Experience as a Forward Deployed Engineer, Staff Engineer, Machine Learning Engineer, or Staff Data Scientist.
- Industry subject-matter expertise.

## Compensation and Benefits
- Competitive compensation with salary and equity.
- Comprehensive medical, dental, and vision coverage for employees and dependents, plus a 401(k).
- Paid parental leave for all new parents, including adoptive and surrogate journeys.
- Relocation support for employees moving to an office location.

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