Lead Data Scientist, Innovation Lab

What the role needs

• PakEnergy is accelerating its innovation. Help us lead it.
• What we've already shipped with Pak AI
• AI-powered lease provision analysis (PakEnergy Land). Embedded AI that flags key lease provisions in seconds instead of hours, so land teams can manage large portfolios and acquisitions faster.
• These are the first steps. The Innovation Lab is where the next ones get found, proven and shipped.
• The Innovation Lab brings together everyone it takes to go from a customer problem to a working product:
• Industry experts for every PakEnergy product: Land, Production, Accounting and Transportation. They know the workflows, the data and the customers firsthand.
• A Lead Applied AI Engineer, your peer, who designs and builds the Lab's generative AI, LLM and agentic systems and gets them into production.
• Solution engineers who take prototypes to customers and into production.
• You, the Lab's founding owner of data science and machine learning.
• Why this role
• Founding owner of your discipline. You'll set the technical direction, standards and practices for data science in the Lab from day one, and help shape what the Lab works on.
• Ownership from prototype to production. You own the data science from problem framing through modeling and evaluation, and see it through customer pilots into production.

From the employer

PakEnergy is accelerating its innovation. Help us lead it. More than 2,300 oil and gas companies run their land, production, accounting and transportation on PakEnergy. We've started putting AI to work across that platform. Now we're accelerating our pace of innovation, and we're building the PakEnergy Innovation Lab to do it. The Lab's mandate is simple: find the highest-value problems our customers face, prove solutions quickly with working prototypes built on real operational energy data, and take what works into production. We're hiring a Lead Data Scientist to be the founding owner of data science and machine learning on the Lab's cross-functional team, reporting directly to our Chief Product Officer. This is a hands-on lead role: you'll build the models and write the code yourself while setting direction for the discipline. You'll have real autonomy. You own the data science approach on Lab projects, help shape the opportunity backlog with the Chief Product Officer and the industry experts, and make the call, backed by evidence, when an idea should stop. We value candor over polish: a fast, well-reasoned "this won't work" is a good outcome. Our data spans several product platforms, and part of the job is spotting the data gaps that limit what we can ship and helping close them. What we've already shipped with Pak AI • AI-powered lease provision analysis (PakEnergy Land). Embedded AI that flags key lease provisions in seconds instead of hours, so land teams can manage large portfolios and acquisitions faster. • PakCAPTURE™ (PakEnergy Transportation). Drivers photograph tickets, receipts and paperwork in the mobile app. Pak AI extracts the key data, auto-populates pickup and drop-off forms, and files the documents with the right load. • OnPing Plunger™ (OnPing). Optimization for plunger-lift wells. Pak AI learns each well's best historical runs, compares actual against expected performance, and tunes setpoints within the operator's automation and safety limits, or flags the well for human review. It has delivered up to 30% more production on conservatively set wells and 3.5–7% on wells that were already well optimized. These are the first steps. The Innovation Lab is where the next ones get found, proven and shipped. The team • The Innovation Lab brings together everyone it takes to go from a customer problem to a working product: • Industry experts for every PakEnergy product: Land, Production, Accounting and Transportation. They know the workflows, the data and the customers firsthand. • A Lead Applied AI Engineer, your peer, who designs and builds the Lab's generative AI, LLM and agentic systems and gets them into production. • Solution engineers who take prototypes to customers and into production. • You, the Lab's founding owner of data science and machine learning. • For a strong data scientist, this means you won't get requirements secondhand, you won't build in a vacuum, and there's a clear path from your model to a customer. Domain experts frame problems with you, your peer lead in applied AI builds the generative AI side, and solution engineers put the results in customers' hands. Why this role • Founding owner of your discipline. You'll set the technical direction, standards and practices for data science in the Lab from day one, and help shape what the Lab works on. • Real operational energy data. You'll work with SCADA and IIoT time series from OnPing, lease and contract documents, revenue and joint-interest accounting, and the tickets and paperwork behind every load hauled, across a customer base of more than 2,300 companies. • Deep expertise around you. You'll work next to industry experts for every product, a peer lead in applied AI and solution engineers, so you can focus on the data science while the team brings domain depth and a route to customers. • Ownership from prototype to production. You own the data science from problem framing through modeling and evaluation, and see it through customer pilots into production. • A direct line to leadership. You report to the Chief Product Officer, and your work shapes the Pak AI roadmap. • A path to leading a team. There are no direct reports today. As Innovation Lab initiatives mature and demonstrate value, this role is set up to help build and lead the Lab's data science team. What you'll do • Frame problems with the industry experts. Partner with the Lab's Land, Production, Accounting and Transportation experts to turn customer pain points into well-defined, measurable data science problems, and size the opportunity. • Own the modeling. Build forecasting, anomaly detection, optimization and predictive models on production, SCADA/IIoT, accounting, transportation and geospatial data, from exploratory analysis through working prototype. • Experiment and evaluate rigorously. Design experiments, offline evaluations and pilot success metrics. Own the evidence on whether something works, and recommend when an idea should stop. • Partner with the Lead Applied AI Engineer on GenAI and agentic work. They design and build the Lab's LLM, document AI and agentic systems. You bring the data, lead evaluation design, and contribute ML and statistical models those systems can use. • Take it to customers and production with solution engineers. Partner on customer pilots, and for the ML models you own, define the data, monitoring and MLOps requirements for a clean handoff to product and engineering teams. • Stay accountable after deployment. Partner with engineering teams on production monitoring, model performance, drift detection and continuous improvement for the models you own after handoff. • Set the technical direction for data science. Define the Lab's data science approach, tooling and standards for data quality, experimentation, reproducibility and responsible ML, and raise data fluency across a cross-functional team. • Build the foundation for a future team. Document how data science works in the Lab, mentor and coach teammates, and shape the roles and hiring plan for when the Lab expands. What you bring • 8+ years in applied ML or data science, including multiple models you built and shipped to production, used by real customers. • A track record of setting technical direction for data science work: choosing the approaches, tooling and standards that others adopted. • Experience mentoring, coaching or leading other data scientists or engineers, formally or as a technical lead. • Depth in at least one of time-series forecasting, anomaly detection or optimization on noisy, real-world data, with strong grounding in statistics, experimental design and model evaluation. • Expert Python and SQL. You're still hands-on and build the models yourself. • Working knowledge of LLM and GenAI systems, especially how to evaluate them (test-set design, metrics, human labeling, error analysis), enough to be a strong technical partner to the Lab's Lead Applied AI Engineer. • Experience working within lightweight, fast-moving software development practices that prioritize rapid experimentation, testing, customer validation and responsible production delivery. • A track record of turning ambiguous problems into shipped products with domain experts, product and engineering, influencing executives and stakeholders along the way, and the candor to say when something won't work. Nice to have • Oil and gas, energy or industrial domain experience is a plus, not a requirement. The Lab's industry experts bring deep knowledge of every PakEnergy product, and you'll learn the domain working beside them. • Experience with SCADA/IIoT or geospatial data, or with labeling and evaluating document-extraction systems. • Databricks, Spark, Azure and/or AWS, and MLflow or similar MLOps tooling. • Experience hiring data scientists or building a data science function from an early stage. • Experience on cross-functional or innovation teams that take prototypes to customers. Education : A degree in a quantitative field or equivalent practical experience. An advanced degree is welcome but not required. Location: In office, Frisco, Texas or Calgary, Alberta. FLSA Status: Exempt (US/Frisco location only). Canadian Employment Classification: Applicable employment classification will be determined in accordance with Alberta employment standards. Benefits : A casual business work environment, generous PTO, employer-sponsored health benefits, and a retirement savings plan (401(k) in the US). Equal opportunity PakEnergy is an equal opportunity employer. We welcome applicants of all backgrounds and are committed to an inclusive hiring process. If you're excited about this role but don't check every box, we'd still like to hear from you.