Azure Data Scientist

Job Title: Remote Data Scientist

Location: Remote

Job Type: Contract

About the Role:

We are seeking an experienced Data Scientist to join our team in the Oil & Gas industry. The ideal candidate will have strong expertise in machine learning, statistical modeling, and cloud computing, with hands-on experience in Azure and/or Google Cloud Platform (GCP). This is a one-and-done interview process for a fast hiring decision.

Key Responsibilities:

• Develop and deploy machine learning models for business decision-making and optimization.
• Work with large, messy datasets and implement data cleaning, validation, and transformation processes.
• Utilize statistical techniques such as regression, clustering, and neural networks to extract insights.
• Collaborate with data engineers, analysts, and business stakeholders to drive data-driven decisions.
• Implement advanced analytics solutions to improve operational efficiency.
• Conduct exploratory data analysis (EDA) and build predictive models using Python, PySpark, or R.
• Deploy models on Azure Machine Learning Services or GCP AI Platform.
• Present findings to non-technical stakeholders through reports and data visualizations.

Required Qualifications:

• Bachelor’s or Master’s Degree in Statistics, Mathematics, Data Science, Computer Science, or a related field.
• 8+ years of experience in data science (for Bachelor’s degree holders) or 5+ years (for Master’s degree holders).
• Proven ability to work with real-world, unstructured data.
• Strong programming skills in Python, R, or SQL for data manipulation and modeling.
• Expertise in Azure Cloud (Azure Data Factory, Synapse, Databricks) or GCP AI/ML services.
• Knowledge of ML algorithms (classification, clustering, regression, neural networks, etc.).
• Experience in ETL/ELT processes and working with large datasets.
• Strong analytical mindset with problem-solving skills.
• Excellent communication skills to translate complex findings into business solutions.

Preferred Qualifications:

• Experience in the Oil & Gas industry or related energy sectors.
• Hands-on experience with ML model deployment at scale.
• Familiarity with Big Data tools like Apache Spark, Hadoop, or Kafka.
• Experience with Deep Learning frameworks (TensorFlow, PyTorch, Keras).