Data Scientist

Posted Yesterday
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Houston, TX, USA
In-Office
Mid level
Logistics • Energy • Industrial • Manufacturing
The Role
Develop predictive and statistical models to forecast turbine downtime, detect anomalies, and identify equipment degradation. Build P&L and operational dashboards, structure SCADA and maintenance data, classify outage events, support root-cause analysis, and recommend reliability improvements. Collaborate with engineering, operations, and asset management while communicating insights to technical and executive stakeholders.
Summary Generated by Built In
Company Description

About Solaris Energy Infrastructure
Solaris Energy Infrastructure, Inc. (NYSE:SEI) provides scalable equipment-based solutions for use in distributed power generation as well as the management of raw materials used in the completion of oil and natural gas wells. Headquartered in Houston, Texas, Solaris serves multiple U.S. end markets, including energy, data centers, and other commercial and industrial sectors.
 

Job Description

 

About the Opportunity
Solaris is seeking a mid-level Data Scientist to support turbine operations and engineering reliability efforts. This role bridges data engineering, statistical/ML modeling, and turbine domain knowledge to improve fleet reliability, reduce unplanned downtime, and provide operational and financial visibility to engineering and business leadership. The ideal candidate is comfortable moving between building dashboards for business stakeholders and developing predictive models for equipment health.

Essential Functions
Reporting & Business Analytics

  • Build and maintain P&L dashboards tracking turbine fleet financial performance, availability, and cost drivers
  • Translate operational data into clear financial and operational KPIs for engineering and business leadership
  • Support monthly/quarterly reporting cycles with accurate, timely data

Downtime & Reliability Data

  • Collect, clean, and structure turbine downtime data from SCADA, CMMS, OEM reporting, and field logs
  • Classify and root-cause downtime events (mechanical, electrical, control system, weather, grid-related, etc.)
  • Maintain a reliable, queryable historical database of outage and maintenance events across the fleet

Predictive Analytics & AI Tools

  • Develop and deploy predictive models (ML-based and statistical) to forecast turbine downtime and component degradation ahead of failure
  • Build anomaly detection and early-warning tools using sensor/operational data (vibration, temperature, pressure, combustion parameters, etc.)
  • Work with engineering to validate model outputs against physical failure modes and OEM guidance
  • Iterate on models as new failure data becomes available; track model performance over time

Reliability Improvement Support

  • Partner with the Reliability Manager and engineering team to identify trends driving forced outages and derates
  • Support root cause analysis (RCA) efforts with data-driven insights
  • Recommend maintenance interval or strategy adjustments based on data trends (RCM/predictive maintenance support)

Cross-Functional Collaboration

  • Work closely with Operations, Engineering, and Asset Management to ensure data pipelines reflect real-world turbine conditions
  • Present findings to technical and non-technical stakeholders, including leadership

Qualifications

Experience/Education

  • Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, or related field (or equivalent experience)
  • 2–5 years of experience in data analysis, with exposure to industrial/energy/manufacturing operations preferred
  • Proficiency in SQL and Python (pandas, scikit-learn, or similar)
  • Experience building dashboards (Power BI, Tableau, or similar)
  • Strong understanding of statistical analysis and predictive modeling techniques
  • Ability to communicate technical findings to non-technical stakeholders
  • Familiarity with time-series forecasting, anomaly detection, or condition-based monitoring techniques
  • Experience with SCADA/historian data (OSIsoft PI, or similar)
  • Exposure to reliability engineering concepts (MTBF, RCM, FMEA)
  • Experience with cloud data platforms (Azure, AWS) and ML deployment pipelines

Key Skills and Qualifications

  • Exceptional communicator – direct and transparent, skilled problem-solver with proven success in building coalitions and avoiding conflicts
  • Total ownership mentality – proactively identifies and removes obstacles across numerous ongoing tasks
  • Independent thinker – provides original thoughts and constantly asking "how can we do this better"
  • Innovative thinker – willingness to consider novel solutions and ability to adapt to change
  • Desirable teammate – impeccable character, humility, and collaborative
  • Relentless – aspires to contribute and achieve his/her full potential

Additional Information

Our CREATORS Culture
At Solaris, we believe that staying true to our core beliefs improves our decision-making, productivity and is key to our individual and collective achievements. Combining your innovative thinking with our core values that encourage Communication, Recognition, Entrepreneurship, Accountability, Teamwork & Transparency, Ownership, Results and Safety, we become CREATORS.

We value your hard work, integrity, and commitment to the Solaris “First in Service & Innovation” culture through competitive pay and benefits packages and ongoing career development.

  • Competitive compensation packages
  • Medical, Dental & Vision benefits
  • Disability Insurance
  • Company paid Life and AD&D insurance with supplemental offerings
  • Company matching 401(k) retirement plan
  • Paid time off, including 10 paid holidays
  • Career Progression
  • Tuition Reimbursement

This job overview is not all inclusive. In addition, Solaris reserves the right to amend this job overview at any time. Solaris is an Equal Opportunity Employer.

Why Solaris Join a company at the forefront of the energy infrastructure buildout powering data centers and industrial growth. We offer competitive compensation, benefits, and opportunities to grow alongside a high-performing team.

Skills Required

  • Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, or a related field, or equivalent experience
  • 2-5 years of experience in data analysis
  • Proficiency in SQL and Python, including pandas and scikit-learn or similar
  • Experience building dashboards using Power BI, Tableau, or similar
  • Strong understanding of statistical analysis and predictive modeling techniques
  • Ability to communicate technical findings to non-technical stakeholders
  • Familiarity with time-series forecasting, anomaly detection, or condition-based monitoring
  • Experience with SCADA or historian data, such as OSIsoft PI
  • Exposure to reliability engineering concepts including MTBF, RCM, and FMEA
  • Experience with cloud data platforms such as Azure or AWS and ML deployment pipelines
  • Experience in industrial, energy, or manufacturing operations
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The Company
471 Employees
Year Founded: 2014

What We Do

Solaris Energy Infrastructure provides proprietary power generation, control, and distribution solutions along with logistics equipment and services. Founded in 2014, the company serves data center, energy, commercial, and industrial customers. Its offerings include rapidly deployable, integrated power infrastructure and specialized automated systems and field services that support efficient, safe oil-and-gas wellsite operations and other critical power workloads across demanding markets.

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