• Define and lead the vision, strategy, and roadmap for data products aligned with business objectives and the company’s data platform. • Translate business and cross-functional team needs into clear data product requirements, with readable data contracts and well-defined consumption patterns. • Prioritize the backlog based on value, effort, and impact, balancing demands from multiple stakeholders. • Partner with Data Engineering, Data Science, AI, and Product teams to enable scalable, reusable deliveries. • Define and track success, adoption, and quality metrics for data products. • Ensure delivered products meet the use cases of consuming teams, including Generative AI applications and autonomous agents. • Safeguard data governance, reliability, and compliance (including LGPD) in collaboration with responsible areas. • Communicate decisions, trade-offs, and roadmap evolution clearly to technical and business audiences.

Role Description The Senior Data Solutions Lead is a strategic, hands-on leadership role responsible for driving the design, development, and implementation of enterprise-scale data architecture and solutions. This individual will serve as the primary technical authority for our data engineering initiatives, bridging the gap between complex business requirements and scalable technical deliverables. The ideal candidate will guide a team of data engineers and analysts, champion best practices in data governance, and ensure that our data infrastructure supports advanced analytics, reporting, and mission-critical applications. - Strategic Leadership: Define and execute the overarching data strategy, ensuring alignment with organizational goals and technology roadmaps. - Architecture & Design: Architect scalable, secure, and highly available data platforms, including data lakes, data warehouses, and streaming data pipelines. - Team Management & Mentorship: Lead, mentor, and grow a cross-functional team of data engineers, developers, and analysts to deliver high-quality data solutions. - Stakeholder Collaboration: Partner with cross-functional business leaders, product managers, and external stakeholders to translate complex business needs into robust technical requirements. - Data Governance & Security: Establish and enforce data quality standards, governance frameworks, and security protocols to protect sensitive information and ensure compliance with relevant regulations. - Technology Evaluation: Continuously assess and recommend new data technologies, tools, and methodologies to optimize performance, reduce costs, and improve data accessibility. - Project Delivery: Oversee the end-to-end lifecycle of data projects, ensuring on-time delivery within Agile frameworks. Qualifications - U.S. Citizen: Must be a US Citizen. - Suitability: Ability to obtain and maintain a DHS Public Trust suitability determination. - Experience: 10+ years of progressive experience in data engineering, data architecture, or related fields, with at least 3 years in a leadership or lead architect role. - Cloud Platforms: Deep expertise in one or more major cloud service providers (AWS, Azure, or Google Cloud Platform) and their respective data ecosystems. - Technical Proficiency: Expert-level knowledge of SQL and programming languages such as Python, Scala, or Java. - Data Integration: Proven experience designing and building robust ETL/ELT pipelines using modern integration tools (e.g., Apache Airflow, dbt, Spark, Kafka). - Data Modeling: Strong proficiency in relational and non-relational database design, dimensional modeling, and data warehousing concepts. - Communication: Exceptional verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. - Stakeholder Management: Ability to effectively communicate and share knowledge with contacts at all levels. Skilled in developing collaborative relationships. - Team Management: Ability to manage multiple projects and priorities across multiple workstreams with tight deadlines in a fast-paced environment. Requirements - Salary Range: 175,000 - 200,000 Benefits - General Description of Benefits

Role Description We are hiring a Data Scientist to lead forecasting and optimization efforts within our platform. Reporting to the Sr. Director of Engineering, this role will define how quantitative models are built, productionized, and integrated into the system’s core functionality. Our DERMS creates and runs virtual power plants (VPPs), requiring forecasting and optimization of delivered capacity in real-world grid environments. This is a senior individual contributor role with broad ownership. You will design and deploy forecasting and optimization systems that directly shape product behavior and operational workflows. The role requires comfort working across the full stack of quantitative development — from raw data plumbing to production deployment. The candidate must have prior experience in electricity and capacity markets; must be knowledgeable in distribution grid topology; and operational boundaries of batteries, EVs, and large commercial buildings. Qualifications - 7+ years of experience in data science, applied statistics, quantitative engineering, or related fields - Real-world experience building electric load forecasting models - Strong understanding of constraint programming and multi-objective optimization for real-time systems - Experience building optimization models and implementing them in energy / capacity markets - Background in time-series analysis and regression-based modeling - Proven experience deploying and maintaining models in production environments - Comfort working with highly variable real-world data from numerous and varying sources, and building the supporting infrastructure - Strong programming skills in Python (or similar) - Ability to operate autonomously and make sound technical trade-offs - Strong communication skills across technical and non-technical audiences Requirements - Experience in the DERMS / VPP space (Nice to Have) - Familiarity with US energy and capacity markets specifically (Nice to Have) - Background in Bayesian modeling (Nice to Have) - Knowledge of distribution grid topology and the operational boundaries of batteries, EVs, and large commercial buildings (Nice to Have) Benefits - Medical insurance - Vision insurance - Dental insurance - Employer paid life insurance, AD&D, and disability insurance - Competitive 401(k) match – up to 6% - Performance based bonus - Potential profit sharing - Paid time off, holidays and other paid leave

• Design, monitor and measure complex A/B tests and experiments to validate business hypotheses, ensuring the statistical robustness of decisions. • Create sales performance metrics for products and develop solutions that improve portfolio profitability. • Develop descriptive and predictive data science solutions focused on process optimization, resource allocation and decision support for health and portfolio performance areas. • Execute all stages of the data science solution lifecycle: business understanding, variable study and preparation, mathematical/statistical modeling, performance validation, support for model deployment to production and measurement of results. • Collaborate with the functional area on the design, use and monitoring of models.