Senior Data Scientist

Join the Market Leader in Electric Power Data and Analytics Solutions

 

The electrical grid is the largest and most complicated machine ever built. Yes Energy’s industry-leading electric power trading analytics software provides real-time visibility into the massive amount of data generated by the North American electrical grid daily. Our unique and innovative view of the data informs real-time trading decisions and mid-to-long-term investment decisions that keep utility prices low, support the energy transition, and keep the grid running. It’s both challenging work and work with a purpose.

 

Be a part of our successful, growing business during international transformation.

 

Position Summary

 

This role is on the Forecasting Data Science team and combines research with productized model delivery in a forecasting SaaS environment. You will partner closely with Forecast Analysts in an operational capacity (daily model configuration, runtime monitoring, exception handling, and customer-impact workflows), along with Product and Engineering, to ensure models are accurate, reliable, and usable in production-grade services. The work spans Python-based libraries and pipelines for data extraction, feature engineering, supervised learning, and robust handoff into operational systems. Fortran experience is not required, but it would be a strong plus when interfacing with legacy algorithms.

 

Position Details

 

• Salary range: RON 180,000 - RON 250,000
• Location: Bucharest, Romania
• Full-time
• Hybrid - 2 days in the office
• Reporting to: Engineering Manager

 

Primary Responsibilities

 

• Research, develop, and improve demand and renewable forecasting and predictive models for current use cases and new market opportunities.
• Apply advanced statistical, machine learning, and time-series methods to energy and weather-driven datasets; ideally, bring direct time-series experience in the energy industry.
• Design, train, and evaluate AI/ML models for time-series forecasting in the energy market and weather-driven applications, including feature engineering, model selection, and performance monitoring.
• Build and evolve evaluation frameworks and experiments to validate model accuracy, stability, and business impact over time.
• Collaborate with Forecast Analysts, Product, and Engineering to make models practical to train, tune, monitor, and reproduce in a SaaS delivery model.
• Lead technical direction for modeling initiatives, including approach selection, quality standards, and trade-off decisions.
• Mentor peers and analysts; raise the quality of experiments, code, documentation, and model operations.
• Partner with Platform/Engineering on scalable implementation patterns for CI/CD, configuration, containers, and integration.
• Drive cross-team initiatives that expand forecasting capability across geographies, asset types, and forecast horizons.
• Communicate assumptions, findings, uncertainty, and trade-offs clearly to technical and non-technical stakeholders.
• Stay current on power market structure, regulatory changes, and technology shifts that influence forecasting requirements.

Minimum Qualifications

 

• Minimum of five years of experience with time-series forecasting
• Graduate degree in Computer Science, Data Science, Mathematics, Engineering, or a related field, or related years of experience
• Strong Python for data science (NumPy, Pandas, scikit-learn, gradient boosting frameworks).
• Hands-on experience applying AI/ML techniques to time-series problems (e.g., forecasting, anomaly detection, probabilistic prediction), ideally in the energy industry.
• Proficiency in backend languages, especially C#
• Strong forecasting and time-series fundamentals, including experimental design and model validation.
• Familiarity with Agile development methodologies.
• Excellent communication and teamwork skills. Passion for sharing knowledge with the rest of your team, building shared tooling, and directly helping customers.
• Self-directed and comfortable supporting the needs of multiple teams, systems, and products.
• Continual learner, engaged in professional development.

 

Preferred Qualifications & Key Competencies

• Fortran is not required; experience collaborating across Python/Fortran boundaries is a valuable plus.
• Demonstrated ability to lead technical initiatives and mentor others in modeling and applied ML engineering practices.
• Experience aligning ML design with system constraints and multi-stakeholder needs in a SaaS product environment.
• Strength in shaping how experimentation, packaging, and deployment practices fit together for dependable delivery.
• Experience with modern AI approaches for time-series modeling (e.g., gradient boosting, deep learning sequence models, hybrid/statistical-ML methods) in production environments.

• Advanced Analytical & Problem Solving – Applies deep expertise in statistical modeling, machine learning, and time-series forecasting to solve complex, ambiguous problems and drive impactful outcomes.
• Technical Execution & Data Science Expertise – Demonstrates strong proficiency in Python-based data science tools, model development, feature engineering, and scalable ML practices within production environments.
• Data Management & Quality – Ensures high standards for data integrity, validation, and reproducibility across datasets, models, and forecasting pipelines.
• Systems Thinking – Understands how models interact within broader systems, including data pipelines, SaaS delivery architecture, and operational forecasting workflows.
• Research & Innovation – Continuously explores new methodologies, tools, and approaches to improve forecasting accuracy, scalability, and business impact.
• Energy Industry & Market Knowledge – Applies knowledge of energy markets, weather drivers, and grid dynamics to inform model development and forecasting strategies.
• Stakeholder Focus – Partners effectively with Forecast Analysts, Product, and Engineering to ensure models meet real-world use cases and customer needs.
• Effective Communication – Clearly communicates technical concepts, model assumptions, trade-offs, and uncertainty to both technical and non-technical audiences.
• Strategic Thinking – Contributes to long-term forecasting strategy, including expanding capabilities across markets, asset types, and forecast horizons.
• Ownership & Initiative – Takes responsibility for model performance, operational reliability, and continuous improvement in a production environment.
• Team Focus & Knowledge Sharing – Collaborates across teams and mentors peers to elevate modeling practices, experimentation quality, and technical standards.
• Prioritization & Operational Efficiency – Balances research, development, and operational support work while driving efficient, scalable processes.

At Yes Energy, we value connecting directly with candidates. We kindly ask that third-party recruiters and agencies not submit resumes, as we are not open to external recruiting partnerships.

ABOUT YES ENERGY

 

Overview

 

Yes Energy delivers real-time market data and electric power trading decision solutions.  Over 1,000 market participants use Yes Energy solutions daily.  The business is a leader in all aspects of information content collection and management, developing and delivering data and market analytics solutions. Since its inception in 2008, Yes Energy has become a trusted and respected supplier of innovative and reliable solutions focused on the needs of power market analysts, traders, and trade managers.  Yes Energy has a team of over 350 amazing professionals in Boulder, CO (HQ); Boston, MA; Chicago, IL; Glendora, CA; Richmond, VA; London, United Kingdom; Auckland, New Zealand; and Bucharest, Romania.

 

Culture

 

Yes Energy has been named one of the Best Places to Work in Colorado, and we have the culture to prove it. At Yes Energy, we care about saying “Yes” to customers. We like to listen, learn, and develop our solutions in line with their needs. We think about customers as business partners, and when we help them be more successful … we are more successful, too.

 

Around the office, our culture is driven by some pretty fundamental values that we’re proud of:

• We love innovation and solving tough challenges;
• We are “high standards people” who combine passion and pride with hard work and rewards of all kinds-- in an ethic that is consistent across the company.
• We’re team-focused with a flat hierarchy-- we work in small teams on well-defined projects that directly impact the success of the business;
• We play to the strengths and experience of each person while each of us also works along a continuum of roles adjacent to our focus area.  This presents the challenge of maintaining a broad set of skills as well as an opportunity to learn and contribute in many ways. 
• We are constantly growing. Professional development happens every day and every year.

 

Compensation and Benefits

 

We offer highly competitive salaries and real bonuses that are achievable and that you can impact. Our benefits package is also very competitive, including medical insurance, a 401 (k) Plan with matching, flexible vacation, and flexible work schedules. Yes Energy encourages and funds investment in both formal and informal professional development.

 

At Yes Energy, we are dedicated to building a diverse, inclusive, and authentic workplace. If you’re excited about this role but your experience doesn’t perfectly align with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.

 

In accordance with Colorado law, the range provided is Yes Energy’s reasonable estimate of the base compensation for this role. The actual amount may be higher or lower based on non-discriminatory factors such as location, experience, knowledge, skills, and abilities.

 

Yes Energy provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, Yes Energy complies with applicable state and local laws governing nondiscrimination in employment in every location where the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.