Principal Data Scientist - 26205

Pearl Street Technologies

Pittsburgh (Allegheny County)

On-site

USD 140,000 - 210,000

Full time

14 days+

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Benefits offered by this job

Medical

Dental

Vision

Income Protection (disability, life/AD

EAP

HSA, Commuter

Lifestyle & Wellbeing Program

Pet Insurance

Job summary

Enverus is seeking a Principal Data Scientist for Power and Renewables to drive data strategy and create measurable customer value. You will partner with Product Management and Engineering to define data roadmaps and apply advanced ML across multiple product areas.

You will lead a team, mentor analysts, and stay at the forefront of data analytics techniques, demonstrating data‑driven culture across the organization.

Qualifications

Bachelor's degree required with 4–6 years of related experience.
Strong background in statistics, machine learning, and data analysis.
Proven ability to lead cross‑functional data initiatives and influence product teams.
Excellent collaboration and communication skills with stakeholders at all levels.

Responsibilities

Lead strategic data analysis initiatives using advanced statistical methods and ML to generate insights.
Collaborate with product managers and engineers to align data work with product strategy.
Assess impact of data initiatives on KPIs, customer outcomes, and business results.
Oversee data governance, security, and compliance within data ops.

Skills

Python

SQL

Advanced data analysis

Machine learning

Leadership

Mentoring

Strategic thinking

Communication

Education

Bachelor's degree in a quantitative field

Bachelor's degree

Tools

Data warehousing

Hadoop/Spark

Cloud platforms (AWS/GCP)

Job description

Description

Principal Data Scientist

Why YOU want this position

At Enverus, we’re committed to empowering the global quality of life by helping our customers make energy affordable and accessible to the world.

We are the most trusted energy‑dedicated SaaS company, with a platform built to maximize value from generative AI, and our innovative solutions are reshaping the way energy is consumed and managed. By offering anytime, anywhere access to analytics and insights, we’re helping our customers make better decisions that help provide communities around the world with clean, affordable energy.

The energy industry is changing fast. But we’ve continued to lead the way in energy technology, creating intelligent connections across the entire energy ecosystem, from renewables, power and utilities to oil and gas and financial institutions. Our solutions create more efficient production and distribution, capital allocation, renewable energy development, investment and sourcing, and help reduce costs by automating crucial business operations. Of course, this wouldn’t be possible without our people, which is why we have built a team of individuals from a diverse range of backgrounds.

Are you ready to help power the global quality of life? Join Enverus, and be a part of creating a brighter, more sustainable tomorrow.

We are currently seeking a Principal Data Scientist for Enverus Power and Renewables, who will create measurable customer value. You will partner closely with Product Management and Engineering to define and execute short‑ and long‑term data roadmaps, applying advanced statistical, machine learning, and data engineering techniques across multiple product areas.

Performance Objectives

Strategic Data Analysis: Lead strategic data analysis initiatives, leveraging advanced statistical techniques, predictive modeling, and machine learning algorithms to uncover valuable insights. Analyze complex data sets to identify patterns, trends, and correlations that inform product strategy, optimization, and innovation.
Product Strategy Alignment: Collaborate closely with product managers, executives, and stakeholders to align data analysis efforts with the overall product strategy. Provide strategic guidance and insights to drive product roadmap prioritization, feature development, and market positioning.
Business Impact Assessment: Assess the impact of product initiatives on key performance metrics, customer satisfaction, and business outcomes. Conduct rigorous analysis to measure the effectiveness of product changes, identify causal relationships, and provide recommendations for continuous improvement.
Data Governance and Infrastructure: Oversee data governance processes, ensuring data integrity, security, and compliance. Collaborate with data engineering and IT teams to optimize data collection, storage, and retrieval processes. Drive improvements in data infrastructure and data management practices.
Thought Leadership and Innovation: Stay at the forefront of data analysis methodologies, tools, and industry trends. Champion innovative approaches to data analysis, experiment design, and modeling techniques. Act as a thought leader in the field of data analytics, influencing the organization’s data‑driven culture.
Stakeholder Collaboration: Collaborate closely with cross‑functional teams, including product managers, engineers, data scientists, and executives, to provide insights and recommendations. Influence decision‑making processes by effectively communicating complex data insights and demonstrating the value of data‑driven strategies.
Team Leadership and Mentorship: Provide leadership and mentorship to the data analytics team. Foster a culture of continuous learning, collaboration, and growth. Guide and mentor junior analysts, helping them develop their analytical skills and business acumen.

Competitive Candidate Profile

Advanced Data Science: Expertise in advanced data analysis techniques, including statistical modeling, predictive analytics, and machine learning. Proficiency in programming languages such as Python, and strong SQL skills for data extraction and manipulation.
Leadership and Influencing Skills: Strong leadership and influencing skills to effectively collaborate with cross‑functional teams, influence decision‑making processes, and drive organizational change.
Ability to inspire and mentor a team of data analysts.
Technical Expertise: Extensive experience in data manipulation, data querying, and database management. Familiarity with data warehousing concepts and data integration processes. Stay updated with emerging technologies and tools in the field of data analytics.
Critical Thinking and Problem‑solving: Strong critical thinking and problem‑solving abilities to tackle complex business challenges, formulate data questions, and derive actionable insights from data analysis.
Ability to identify key business opportunities and make data‑driven recommendations.
Strategic Vision and Innovation: Demonstrated ability to think strategically and envision the future of data analytics in the organization.
Proactively seek innovative approaches to data analysis, experiment design, and modeling techniques.
Collaboration and Relationship Building: Excellent collaboration and relationship‑building skills to establish strong partnerships with product managers, executives, and stakeholders. Work effectively in a team‑oriented, dynamic environment.
Data Governance and Compliance: In‑depth knowledge of data governance best practices, data security, and regulatory compliance. Ability to ensure data integrity, privacy, and compliance with relevant data protection regulations.

Required experience