Data Science Team Lead

Salary: 20. 000 - 25. 000 RON net per month

• ● 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).
• ● Proven experience managing direct reports in a data science, machine learning, analytics, forecasting, or software engineering environment.
• ● Experience leading a technical team through delivery of production-grade models, data products, analytics systems, or SaaS capabilities.
• ● Hands-on experience applying AI/ML techniques to time-series problems (e. g. , forecasting, anomaly detection, probabilistic prediction), ideally in the energy sector.
• ● 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.

• Position Summary
• This is a team lead position on the Forecasting Data Science team, combining hands-on data science leadership with direct people management responsibility. This role is responsible for managing a growing team, setting priorities, supporting performance management, and driving execution across cross-functional stakeholders. 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. Fortran experience is strongly preferred since it would be beneficial when interfacing with legacy algorithms. Success in this role requires both strong applied forecasting and machine learning expertise and proven people-management skills, including experience leading direct reports, providing feedback and aligning individual work with team and business priorities.
• Primary Responsibilities
• ● Research, develop, and improve demand and renewable forecasting and predictive models for current use cases and new market opportunities.
• ● Balance hands-on technical contribution with people leadership, ensuring the team delivers high-quality forecasting models, reliable operations, and scalable model-development practices.
• ● 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.

• AI
• Backend
• C#
• CI/CD
• Fortran
• Support
• Machine Learning
• Python
• REST
• numpy
• pandas
• . NET Framework
• AWS
• Azure
• Data-Science
• PyTorch
• Snowflake

More:

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, as well as in 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 200 amazing professionals located across the United States, Europe and Asia.

Culture
At Yes Energy we care about saying “Yes” to customers. We like to listen and learn, and develop our solutions in line with our customers’ needs. We think about customers as business partners and when we help them to 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 a 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 includes private medical insurance, wellness/gym benefits, flexible vacation, and flexible work schedules.
● Yes Energy encourages and funds investment in both formal and informal professional development.

Yes Energy provides equal employment opportunities to all employees and applicants without regard to race, color, religion, sex, national origin, age, disability, genetics, or any other protected status. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, compensation, and training.

last updated 22 week of 2026