Quick Overview
Job Description
Hi,
Hope you are doing well,
Please find the job description given below and let me know your interest.
Position: Senior Data Scientist – Oil & Gas Analytics (Onsite)
Location: Brentwood, TN (Onsite Day 1, Relocation Works)
Duration : 6+ months
Job Description:
Key Responsibilities
· Business Problem Solving & Stakeholder Engagement
· Partner with business stakeholders and subject matter experts across the organization to identify, prioritize, and solve high-value business problems using data science and machine learning.
· Translate business challenges into analytical, predictive, and optimization solutions.
· Develop a strong understanding of business processes, operational workflows, and key performance drivers.
· Communicate analytical findings and recommendations to both technical and non- technical audiences.
· Present insights in a manner that supports informed business decision-making and measurable outcomes.
Required Qualifications & Experience
· Bachelor's or Master's degree in data science, Computer Science, Statistics, Mathematics, Engineering, Operations Research, or a related quantitative field.
· 7+ years of hands-on experience in Data Science, Advanced Analytics, or Machine Learning.
· 3+ years of experience within the Oil & Gas industry, including exposure to operational, commercial, engineering, or industrial data environments.
· Proven experience developing and deploying machine learning models that deliver measurable business value.
· Experience working directly with business stakeholders to understand requirements, define analytical approaches, and communicate results.
· Demonstrated ability to independently acquire, analyze, cleanse, transform, and prepare data for analytical and machine learning initiatives.
· Experience partnering with Data Engineering teams to transition analytical solutions into scalable production environments.
· Strong problem-solving skills with the ability to work effectively in ambiguous business environments and with incomplete or imperfect datasets.
Oil & Gas Experience (Mandatory)
· Candidates must possess hands-on experience within the Oil & Gas Industry or Manufacturing Industry and demonstrate the ability to apply data science and machine learning techniques to solve operational, commercial, engineering, maintenance, reliability, supply chain, or optimization challenges.
· Experience working with operational and industrial datasets such as process data, historian data, maintenance data, supply chain data, logistics data, or other industry-specific data sources is strongly preferred.
Preferred Skills & Technologies
· Microsoft Azure, Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure Machine Learning, Databricks, Apache Spark / PySpark
· Python, Pandas, NumPy, SciPy, Scikit-Learn, Statsmodels, Notebooks
· XGBoost, LightGBM, TensorFlow, PyTorch, Time-Series Forecasting Frameworks, Optimization Techniques, Simulation Modeling, Statistical Modeling
· Power BI, Plotly, Matplotlib, Seaborn
· Data Modeling, ETL / ELT Concepts, Data Warehousing, Data Quality Management, Feature Engineering, Metadata Management, Data Governance Principles
· Git, GitHub, Azure DevOps, CI/CD Pipelines, Model Monitoring, Model Versioning, API Development
· PI Historian / AVEVA PI System, SCADA Systems, Distributed Control Systems (DCS), Industrial IoT Platforms, Operational Telemetry Data, Process Control Data, Reliability and Maintenance Systems, SAP Data Sources
· Predictive Maintenance, Asset Reliability, Process Optimization, Yield Optimization, Energy Efficiency & Management, Supply Chain Analytics, Logistics Optimization, Demand Forecasting, Inventory Optimization, Operational Performance Analytics, Root Cause Analysis, Risk Modeling
If you are interested, please share your updated resume and suggest the best number & time to connect with you.
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