Data Scientist (Oil & Gas Industry) - CodeByte

Our client CodeByte is hiring a Data Scientist (Oil & Gas Industry) in Lahore.

Position Title: Data Scientist

Industry: Oil & Gas
Experience Required: 5–8 Years
Employment Type: Contract (Minimum 1-Year Engagement)
Department: Digital Transformation / Data & Analytics
Salary: 2500 USD to 3000 USD

Position Overview
We are seeking an experienced Data Scientist with 5–8 years of hands-on experience in advanced analytics, machine learning, and data-driven decision-making, preferably within the Oil & Gas industry. The ideal candidate will leverage large-scale operational, production, drilling, reservoir, maintenance, and sensor data to develop predictive models, optimize business processes, and deliver actionable insights that improve operational efficiency, asset reliability, safety, and profitability.
This is a minimum one-year contractual assignment with potential for extension based on project requirements and performance.
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Key Responsibilities:

Data Science & Analytics

• Design, develop, and deploy machine learning and statistical models to solve complex business and operational challenges.
• Analyze structured and unstructured datasets from drilling, production, reservoir, maintenance, SCADA, IoT, and enterprise systems.
• Build predictive and prescriptive analytics solutions for:[ul data=1]
• Production optimization
• Predictive maintenance
• Equipment failure prediction
• Reservoir performance analysis
• Drilling optimization
• Energy consumption optimization
• Asset integrity management

Develop forecasting models for production, demand, and operational planning.Perform exploratory data analysis (EDA) and feature engineering on large datasets.Evaluate and improve model performance using industry-standard metrics.
Data Engineering & Deployment

• Collaborate with data engineers to build scalable data pipelines and analytical solutions.
• Deploy machine learning models into production environments.
• Monitor model performance and implement continuous improvement processes.
• Work with cloud-based analytics platforms and MLOps frameworks.

Business & Stakeholder Engagement

• Translate business requirements into analytical solutions.
• Present findings, insights, and recommendations to technical and non-technical stakeholders.
• Partner with engineers, geoscientists, operations teams, and business leaders to identify value-generating use cases.
• Support digital transformation initiatives across upstream, midstream, or downstream operations.

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Required Technical Skills:

Data Science & Machine Learning

• Strong expertise in:[ul data=1]
• Supervised and Unsupervised Learning
• Regression and Classification Models
• Clustering Techniques
• Time Series Forecasting
• Anomaly Detection
• Predictive Analytics
• Deep Learning (preferred)

Experience with machine learning libraries:[ul data=1]Scikit-learnTensorFlowPyTorchXGBoostLightGBM
Programming & Data Analysis

• Advanced proficiency in:[ul data=1]
• Python
• SQL

Experience with:[ul data=1]PandasNumPySciPyJupyter Notebooks
Data Visualization & Reporting

• Hands-on experience with:[ul data=1]
• Power BI
• Tableau
• Matplotlib
• Seaborn
• Plotly

Ability to create executive-level dashboards and reports.
Big Data & Cloud Technologies

• Experience working with:[ul data=1]
• Azure, AWS, or Google Cloud Platform
• Databricks
• Apache Spark
• Hadoop ecosystem (preferred)

Familiarity with MLOps tools:[ul data=1]MLflowAzure MLKubeflowDockerKubernetes
Oil & Gas Domain Knowledge

• Understanding of Oil & Gas operational processes, including:[ul data=1]
• Upstream exploration and production
• Reservoir engineering concepts
• Drilling operations
• Production monitoring
• Asset performance management
• Predictive maintenance strategies

Experience working with industrial data sources such as:[ul data=1]SCADA SystemsHistorian DatabasesIoT SensorsERP/EAM Systems (SAP, Maximo, etc.)[center][/center]
Required Qualifications

• Bachelor's or Master's degree in:[ul data=1]
• Data Science
• Computer Science
• Statistics
• Mathematics
• Engineering
• Artificial Intelligence
• Related quantitative discipline

5–8 years of professional experience in Data Science, Advanced Analytics, or Machine Learning roles.Prior experience in the Oil & Gas, Energy, Petrochemical, or Industrial sectors is highly preferred.[center][/center]
Soft Skills & Competencies

• Strong analytical and problem-solving capabilities.
• Excellent communication and presentation skills.
• Ability to explain complex analytical concepts to business stakeholders.
• Strong stakeholder management and collaboration skills.
• Critical thinking and business acumen.
• Self-motivated and capable of working independently.
• Ability to manage multiple priorities and meet deadlines.
• Strong documentation and reporting skills.
• Team-oriented mindset with a collaborative approach.
• Adaptability to dynamic project environments.

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Preferred Certifications

• Microsoft Certified: Azure Data Scientist Associate
• AWS Certified Machine Learning Specialty
• Google Professional Machine Learning Engineer
• Databricks Certified Data Scientist
• TensorFlow Developer Certificate
• Relevant Oil & Gas analytics certifications (preferred)

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Contract Duration
Minimum Contract Duration: 12 Months (1 Year)
Extension: Subject to project requirements and performance.
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Success Criteria
The successful candidate will demonstrate the ability to deliver measurable business value through advanced analytics, predictive modeling, and AI-driven solutions that improve operational efficiency, reduce downtime, optimize production, and support data-driven decision-making within the Oil & Gas environment.