Data Scientist

Recenso Services; Abu Dhabi Emirate; On-site; USD 80,000 - 150,000; Full time

Job summary

An established industry player in the Oil and Gas sector is seeking a Data Scientist to spearhead advanced analytics initiatives. This role involves leveraging data-driven insights to optimize business processes and improve operational efficiency. You will build predictive models, deploy machine learning algorithms, and lead a team to tackle complex challenges. The ideal candidate will have a strong background in data science, particularly within the Oil and Gas industry, and will be adept at communicating technical findings to non-technical stakeholders. Join a forward-thinking company where your contributions will drive significant impact across various domains.

Qualifications

• 7+ years of experience in data science, with 3+ years in Oil and Gas.
• Advanced degree in Data Science or related field required.

Responsibilities

• Drive advanced analytics initiatives in Oil and Gas.
• Lead team to build predictive models and deploy algorithms.

Skills

Machine Learning

Statistical Modeling

Data Engineering

Problem-Solving

Communication

Education

Master’s or PhD in Data Science

Bachelor’s in Computer Science

Tools

Python

R

MATLAB

SQL

TensorFlow

PyTorch

Hadoop

Spark

Power BI

Tableau

Job description

As a Data Scientist for the Oil and Gas Industry, you will drive advanced analytics initiatives, leveraging data-driven insights to optimize various business processes, improve operational efficiency, and solve complex challenges. Your role will involve building predictive models, deploying machine learning algorithms, and leading a team to address key challenges across a wide range of industries.

Technical Responsibilities :

Data Strategy and Management :

• Define and implement data strategies to support business objectives across various domains.
• Oversee data collection, cleaning, and integration from diverse sources (e.g., sensors, transactional data, logs).
• Ensure data accuracy, consistency, and security while adhering to relevant compliance standards.

Model Development and Deployment :

• Design and implement advanced machine learning models (e.g., predictive maintenance, process optimization).
• Develop algorithms for data interpretation, trend analysis, and forecasting.
• Optimize workflows using natural language processing (NLP) for unstructured data, such as reports and logs.

Advanced Analytics :

• Conduct exploratory data analysis (EDA) to identify trends, anomalies, and optimization opportunities.
• Utilize geospatial analysis and statistical techniques to interpret complex datasets.
• Implement real-time data analytics for operational monitoring and performance enhancement.

Technology Leadership :

• Lead the adoption of cloud-based data platforms (e.g., Azure, AWS, Google Cloud) for scalable computation.
• Stay updated on emerging technologies, such as edge computing, digital twins, and advanced AI techniques.
• Drive automation of repetitive tasks using advanced scripting and machine learning pipelines.

Team Collaboration and Leadership :

• Mentor junior data scientists and engineers, fostering a culture of innovation and excellence.
• Collaborate with cross-functional teams to translate business challenges into data science solutions.
• Communicate technical findings to non-technical stakeholders through visualizations and reports.

Optimization and Decision Support :

• Develop optimization models for operational efficiency, cost reduction, and resource allocation.
• Enhance accuracy and reduce downtime through predictive analytics for maintenance and troubleshooting.
• Implement risk assessment models to improve safety, security, and compliance standards.

Tool and Technology Expertise :

• Expertise in Python, R, MATLAB, and SQL for statistical modeling and data analysis.
• Proficient in machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and big data tools (e.g., Hadoop, Spark).
• Hands-on experience with visualization tools like Power BI, Tableau, or D3.js.
• Familiarity with domain-specific software and tools for industry-specific data analysis.

Qualifications :

• Advanced degree (Master’s or PhD) in Data Science, Computer Science, Engineering, Statistics, or a related field.
• 7+ years of experience in data science, with at least 3 years in the Oil and Gas Industry.
• Strong understanding of data systems, operational workflows, and industry-specific challenges.
• Proven success in leading data-driven projects and initiatives.

Key Skills :

• Deep knowledge of machine learning, statistical modeling, and advanced analytics techniques.
• Strong programming and data engineering skills.
• Understanding of the full data lifecycle, from collection and cleaning to modeling and visualization.
• Excellent problem-solving, communication, and leadership abilities.
• Proven track record of innovation in data science applications.

Mandatory Requirements :

• Proven experience in the Oil and Gas industry.
• Presence onsite is required for the role. Candidates based in the UAE or looking to relocate to the UAE will be considered.