Senior Data Scientist, Energy Storage Analytics

Eneon ES Inc.; United States; Remote; CAD 110,000 - 170,000; Full time

Job summary

Eneon ES Inc. seeks a Sr. Data Scientist to transform operational telemetry into reliable data systems, defining Eneon’s data strategy and owning full lifecycle from raw data to production deployment.

The role spans data science and data engineering and requires leadership across cross-functional teams. You will drive end-to-end data science work, develop predictive models for fleet reliability, and deploy analytics into production for decision support.

Qualifications

• 8–15 years of applied experience with operational data from physical systems.
• Bachelor’s degree in a quantitative discipline; Master/Ph.D. preferred.
• Experience with time series data and noisy sensor streams.
• Proficiency with Python for data analysis and modeling.
• Strong SQL skills and relational database experience.

Responsibilities

• Define and own Eneon’s operational telemetry data strategy from raw data to analytics-ready datasets.
• Design retention policies, data resolution, and aggregation for analytics and reporting.
• Lead end-to-end data science work: preprocessing, modeling, training, evaluation.
• Develop predictive models for reliability, maintenance, and forecasting.
• Deploy models and analytics into production environments for inference and dashboards.
• Collaborate with engineering, product, and operations to translate data into actions.

Skills

Time series databases

Python

SQL

Data pipelines

Predictive modeling

Independent work

Communication

Statistics

Analytics architecture

Time series analysis

Education

Bachelor’s degree in a quantitative discipline

Master’s degree or Ph.D. preferred

Tools

InfluxDB

TimescaleDB

OSIsoft PI

Grafana

Plotly

Job description

Eneon ES Inc. seeks a Sr. Data Scientist to transform operational telemetry into reliable data systems, defining Eneon’s data strategy and owning full lifecycle from raw data to production deployment.

The role spans data science and data engineering and requires leadership across cross-functional teams. You will drive end-to-end data science work, develop predictive models for fleet reliability, and deploy analytics into production for decision support.