Senior Data Scientist - Oil and Gas

AiElements; Dhahran Compound; On-site; SAR 120,000 - 150,000; Full time

Job summary

A leading data science firm in Dhahran Compound is seeking a highly skilled Data Scientist to transform complex data into insights. The role includes building predictive models and working closely with business stakeholders to solve data-driven problems. Candidates should have a strong foundation in statistics, machine learning, and proficiency in Python and SQL. The position offers opportunities for both Junior and Senior levels and is set in the dynamic context of the Eastern Province, Saudi Arabia.

Qualifications

• Strong foundation in statistics, probability, and hypothesis testing.
• Experience with data pre-processing, feature engineering, and model tuning.
• Hands-on experience with ML libraries such as TensorFlow and PyTorch.

Responsibilities

• Analyze large and complex datasets to extract insights and trends.
• Build and evaluate machine learning models for business use cases.
• Design and implement feature engineering and data preparation pipelines.

Skills

Strong analytical and problem-solving mindset

Experience with machine learning algorithms

Proficiency in Python and/or R

Strong knowledge of SQL

Ability to interpret models and explain results

Tools

Pandas

SQL

Power BI

Tableau

TensorFlow

PyTorch

Jupyter Notebooks

Job description

We are seeking a highly skilled Data Scientist with a strong foundation in statistics, machine learning, and data analysis to extract actionable insights and build predictive models that support business and operational decision-making. The role focuses on transforming complex data into meaningful trends, patterns, and forecasts while collaborating closely with business stakeholders, analysts, and data engineers.

Key Responsibilities

• Analyze large and complex datasets to extract insights, trends, and predictive patterns.
• Build, evaluate, and interpret machine learning models for real-world business and scientific use cases.
• Perform data wrangling, cleaning, and pre-processing using tools such as Pandas, SQL, and Spark.
• Design and implement feature engineering and data preparation pipelines.
• Apply supervised and unsupervised learning techniques, including:
  • Regression
  • Classification
  • Anomaly detection
  • Time series forecasting
• Apply statistical analysis, hypothesis testing, and experimental design techniques, including A/B testing.
• Work with time series data to develop forecasting and trend analysis models.
• Collaborate closely with business stakeholders to translate business problems into data science solutions.
• Partner with data engineers to support data pipelines, model deployment, and data availability.
• Develop clear visualizations and dashboards to communicate findings using tools such as Power BI, Tableau, and Python visualization libraries.
• Document methodologies, assumptions, and outcomes to ensure transparency and reproducibility.

Required Qualifications & Skills

• Strong foundation in statistics, probability, and hypothesis testing.
• Solid understanding of machine learning algorithms and modeling techniques.
• Proficiency in Python and/or R, including Jupyter Notebooks.
• Experience with data pre-processing, feature engineering, and model tuning.
• Strong knowledge of SQL and relational data structures.
• Hands-on experience with ML libraries such as:
  • TensorFlow
  • PyTorch
• Strong analytical and problem-solving mindset.
• Ability to interpret models and explain results to non-technical stakeholders.
• Strong business and domain understanding to ensure insights are actionable and relevant.

Preferred / Additional Skills

• Experience with Big Data technologies such as Hadoop and Apache Spark.
• Knowledge of experimental design, A/B testing, and causal inference.
• Experience in data visualization using:
  • Power BI
  • Tableau
  • Matplotlib / Seaborn
• Familiarity with data pipelines and production environments.
• Experience working in enterprise-scale or Oil & Gas environments is a strong plus.
• Ability to work cross-functionally with:
  • Business stakeholders
  • Analysts
• Strong communication and documentation skills.
• Ability to manage multiple priorities in a fast-paced environment.
• Continuous learner with a strong interest in emerging data science techniques.
• Open for Junior and Senior levels (based on experience and assessment).