

AptivaCorp
Data Scientist With Oil & Gas Domain Exp
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with Oil & Gas domain experience, based in Houston, Texas, for a 6+ month contract at a pay rate of "unknown." Key skills include Python, SQL, and machine learning frameworks.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
June 25, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
On-site
-
📄 - Contract
W2 Contractor
-
🔒 - Security
Unknown
-
📍 - Location detailed
Houston, TX
-
🧠 - Skills detailed
#Libraries #Deployment #ADF (Azure Data Factory) #Scala #Synapse #ML (Machine Learning) #Python #Data Science #Data Engineering #Telematics #Visualization #Azure Databricks #GIT #Model Validation #Data Quality #Forecasting #Azure SQL #SQL (Structured Query Language) #Azure Machine Learning #Azure Synapse Analytics #DevOps #Microsoft Azure #Monitoring #Data Lake #Azure Data Factory #TensorFlow #PyTorch #Azure #Databricks #IoT (Internet of Things) #BI (Business Intelligence) #Microsoft Power BI #Datasets
Role description
Job Title : Data Scientist With Oil & Gas Domain exp
Location : Houston, Texas-Onsite(M-F)
Position : 6+Month Contract
Need Oil & Gas Domain exp
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
Please share your resume & the below details to process your profile to the Client
Full Name:
Work Authorization/ Visa Status:
Passport Number:
Availability:
LinkedIn:
Current Location:
Available to work onsite in TX:
Best Contact Number:
Currently Working:
Reason for Change of employment:
DOB MMDD:
SSN Last four digits:
Highest Education / University & Year:
Skill Matrix:
Total years of exp as Data Scientist:
Total years of exp in Oil & Gas :
Total years of exp in machine learning :
Total years of exp in SQL :
Total years of exp in Azure:
Job Title : Data Scientist With Oil & Gas Domain exp
Location : Houston, Texas-Onsite(M-F)
Position : 6+Month Contract
Need Oil & Gas Domain exp
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
Please share your resume & the below details to process your profile to the Client
Full Name:
Work Authorization/ Visa Status:
Passport Number:
Availability:
LinkedIn:
Current Location:
Available to work onsite in TX:
Best Contact Number:
Currently Working:
Reason for Change of employment:
DOB MMDD:
SSN Last four digits:
Highest Education / University & Year:
Skill Matrix:
Total years of exp as Data Scientist:
Total years of exp in Oil & Gas :
Total years of exp in machine learning :
Total years of exp in SQL :
Total years of exp in Azure:






