Senior Data Scientist

Jobtailor; Boston (MA); On-site; USD 140,000 - 200,000; Full time

Job summary

Jobtailor is seeking a Senior Analytics Scientist to design and implement rigorous analytics for battery energy storage systems (BESS). You will work with data from BMS telemetry and SCADA, build predictive models, and translate complex results into actionable guidance for asset owners and operators.

The role requires 5+ years in the energy sector, deep BESS expertise, and strong Python/ML skills. You will collaborate with software teams and customers, contributing to production deployments and

Qualifications

• 5+ years of experience in the energy industry, with a focus on battery energy storage systems
• Strong understanding of BESS operation, state estimation, thermal management, degradation, and lifecycle management
• Experience working with large-scale BESS datasets (BMS telemetry, SCADA, event logs, high-frequency time series)
• Proven ability to translate operational challenges into analytical solutions for asset owners/operators
• Proficiency in Python and modern data science libraries (pandas, NumPy, scikit-learn, TensorFlow/PyTorch)
• Solid grounding in statistics, ML, and applied AI with real-world deployment experience
• Experience with time-series analysis, signal processing, anomaly detection, forecasting, and predictive modeling
• Experience with version control (Git) and collaborative software development practices
• Ability to communicate complex analytics to technical and non-technical stakeholders
• Experience collaborating with software engineering teams in production environments (APIs, services, deployment pipelines)
• Strong autonomy and ownership in technically challenging problem spaces

Responsibilities

• Lead design and development of analytic solutions using extensive operational data
• Collaborate with software, product, and customers to translate challenges into analytical solutions
• Identify and prioritize high-impact analytics for BESS performance, health, and revenue
• Develop advanced data science solutions from concept to production
• Explain methods, assumptions, and results clearly to stakeholders
• Support product, sales, and customer success as a BESS SME
• Stay current with battery science, modeling, and ML for energy systems

Skills

Python

Time-series analysis

Statistics

Machine learning

Data science

ML deployment

Tools

Git

APIs

Deployment pipelines

SCADA

BMS Telemetry

Job description

Responsibilities

• Lead the design and development of scientifically rigorous analytics solutions leveraging Power Factors' extensive operational data
• Collaborate closely with software development teams, product management, and technically sophisticated customers to translate real-world operational challenges into robust analytical solutions
• Identify, evaluate, and prioritize high-impact advanced analytics opportunities focused on BESS performance, health, and revenue optimization
• Lead the development of advanced data science solutions from concept through production deployment
• Engage directly with technically sophisticated customers to explain analytical methods, assumptions, and results with clarity and precision
• Serve as an internal BESS subject matter expert, supporting product, sales, and customer success teams with domain guidance
• Stay current with advances in battery science, electrochemical modeling, grid storage economics, and ML for energy systems

Requirements

• 5+ years of experience in the energy industry, with a strong emphasis on utility-scale battery energy storage systems
• Deep, hands‑on understanding of BESS operation, performance, state‑of‑charge and state‑of‑health estimation, thermal management, degradation mechanisms, and lifecycle management
• Demonstrated experience working with large-scale operational BESS datasets, including BMS telemetry, SCADA, event logs, cycle data, and high-frequency time series
• Proven experience developing analytical solutions used by asset owners, operators, integrators, or OEM‑adjacent organizations to support operational and strategic decision‑making
• Proficiency in Python and modern data science libraries (pandas, NumPy, scikit‑learn, TensorFlow / PyTorch, etc.)
• Strong grounding in statistics, machine learning, and applied AI, with demonstrated real‑world deployment experience
• Experience with time‑series analysis, signal processing, anomaly detection, forecasting, and predictive modeling in industrial or electrochemical contexts
• Experience with version control (Git) and collaborative software development practices
• Ability to clearly communicate complex analytical concepts, assumptions, and results to both technical and non‑technical stakeholders
• Experience working closely with software engineering teams in production environments (APIs, services, deployment pipelines)
• Proven ability to translate operational challenges and customer needs into analytically sound and implementable solutions
• High degree of autonomy and ownership in complex, technically ambiguous problem spaces
• Strong scientific rigor, intellectual curiosity, and attention to detail
• Comfort working on long‑horizon, technically demanding problems where analytical quality and robustness are critical

Core Competencies

Demonstrates expertise in Battery Energy Storage Systems (BESS) operations, advanced analytics, and data science methodologies, with a strong ability to communicate complex concepts to diverse stakeholders. Proven track record in developing analytical solutions that drive operational and strategic decision‑making in the energy sector.

Tools & Technologies

• BMS Telemetry
• SCADA
• Version Control (Git)
• APIs
• Deployment Pipelines