Data Scientist with Oil & Gas domain exp // Houston, TX Onsite M-F // Contract
Mohan Sai Ram Gurram
Job Title: Data Scientist with Oil & Gas domain exp
Location: Houston, TX M-F
Duration: Contract
Must Have: Oil & Gas domain exp
H1B/H4-EAD PP No. Mandatory
No Thirdparty GC
Industry: Energy / Natural Gas Compression
Position Overview
Archrock is seeking a Data Scientist to help transform operational data into strategic business insights across our natural gas compression fleet. This role will focus on leveraging telematics, sensor, and operational data to identify trends, improve asset performance, and develop predictive and forecasting models that drive business decisions.
The ideal candidate combines strong data science and machine learning expertise with a passion for solving real-world operational challenges. You will work closely with business stakeholders, engineering teams, operations leaders, and technology teams to build scalable analytics solutions utilizing Archrock's Microsoft Azure ecosystem.
Key Responsibilities
- Analyze large-scale telematics, IoT, sensor, and operational datasets from natural gas compression equipment to uncover actionable insights and trends.
- Develop, deploy, and maintain predictive machine learning models that improve operational efficiency, asset reliability, and business performance.
- Build forecasting models to support maintenance planning, equipment utilization, fleet optimization, capacity planning, and operational decision-making.
- Identify patterns and anomalies within equipment performance data to proactively reduce downtime and improve asset availability.
- Collaborate with operations, engineering, and business stakeholders to translate business challenges into data science solutions.
- Design and implement statistical models, machine learning algorithms, and advanced analytical techniques to solve complex business problems.
- Develop dashboards and visualizations that communicate insights and recommendations to technical and non-technical audiences.
- Partner with data engineering teams to ensure data quality, accessibility, and scalability across analytical platforms.
- Optimize data structures and SQL environments to support machine learning and advanced analytics workflows.
- Support the deployment, monitoring, and continuous improvement of machine learning models in production environments.
Required Qualifications
Must Have
- Experience leveraging telematics, IoT, equipment sensor, or operational data to uncover actionable business insights and performance trends.
- Proven experience building predictive models and forecasting models in a production environment.
- Strong experience applying machine learning techniques to solve real-world business challenges.
- Advanced proficiency in Python for data science and machine learning applications.
- Strong knowledge of machine learning frameworks and libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar.
- Experience with statistical analysis, predictive analytics, time-series forecasting, and model validation techniques.
- Strong SQL skills and experience designing or optimizing database structures that support analytical workloads.
- Experience developing data visualizations and presenting findings to business stakeholders.
- Ability to work independently with stakeholders to define use cases and deliver measurable business outcomes.
Preferred
- Experience in Oil & Gas, Energy, Natural Gas Compression, Industrial Equipment, Manufacturing, Asset Management, Fleet Operations, or Industrial IoT environments.
- Experience working with telematics, SCADA, historian, equipment performance, maintenance, or operational technology (OT) datasets.
- Experience deploying machine learning solutions within Microsoft Azure environments.
Technical Environment
- Microsoft Azure
- Azure Machine Learning
- Azure Data Factory
- Azure Synapse Analytics
- Azure Databricks
- Azure Data Lake
- Azure SQL
- Power BI
- Python
- SQL
- Machine Learning Frameworks
- Scikit-learn
- TensorFlow
- PyTorch
- XGBoost
- Git / DevOps