Data Scientist

Job Title: Data Scientist, Expert - GRID

Contract Duration: 6 Months

Pay range: $105 - 120/hr

Work Type: Hybrid, 2-3 days per week onsite

Location: Oakland, CA

Top Things:

• Ability to build models around data using Python or R
• Ability to get up to speed quickly
• Ability to access data systems to extract data including SAP
• Ability to review data and come up with their own conclusions

Position Overview:

Our client is seeking a talented and driven Data Scientist to join our team. The ideal candidate will be responsible for building predictive models to analyze work and resource planning, forecasting task durations, and identifying opportunities to improve efficiency and safety in substation operations. This role will involve analyzing a variety of data sources, including scheduling, productivity, and weather event data, to develop robust forecasting models and predictive analytics.

Key Responsibilities:

• Predictive Modeling: Develop and implement machine learning models to predict task durations, resource needs, and potential human errors in substation work.
• Data Analysis: Analyze historical work data, scheduling information, crew productivity, weather impacts, and other relevant factors to identify patterns and insights.
• Forecasting: Build advanced forecasting models to improve planning accuracy for substation work, considering dynamic variables such as weather events and crew efficiency.
• Anomaly Detection: Create algorithms to detect anomalies and predict human errors, providing actionable insights to improve safety and performance.
• Opportunity Identification: Use data-driven approaches to highlight opportunities for process improvement and efficiency gains.
• Cross-functional Collaboration: Work closely with operations, engineering, and planning teams to integrate analytical insights into decision-making processes.
• Reporting & Visualization: Develop clear and effective data visualizations and reports to communicate findings to stakeholders.
• Continuous Improvement: Stay up-to-date with the latest trends and advancements in data science, machine learning, and predictive analytics to ensure our methodologies remain cutting-edge.

Required Qualifications:

• Education: Master’s or PhD in Data Science, Systems Engineering, Computer Science, Statistics, or a related field.
• Experience: Minimum 3-5 years of experience in data science, with a focus on predictive analytics, machine learning, and operations analysis.

Technical Skills:

• Proficient in Python, R, SQL, and data analytics tools.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong knowledge of predictive modeling, statistical analysis, and time series forecasting.
• Familiarity with data visualization tools (e.g., Tableau, Power BI, matplotlib).

Domain Knowledge: Experience in the energy sector, utilities, or substation operations is a plus.

Analytical Thinking: Ability to translate complex data into actionable insights.

Communication Skills: Strong ability to communicate complex analytical results to both technical and non-technical audiences.

Preferred Qualifications:

• Experience with predictive maintenance and asset management in industrial settings.
• Familiarity with scheduling and resource planning tools.
• Knowledge of weather forecasting integration into operational models.

Note:

• A client laptop will be provided.
• Local candidates only.