This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Zonda is looking for a passionate Econometrician to help create, evolve and expand our team. This is a high-impact, cross-functional role designed for a "hybrid" thinker: someone with the rigorous economic intuition to develop defensible market theses and the technical "Data Science" chops to build scalable, automated production models. - Improve our core forecasts. - Take ownership of improving and evolving our forecasting models across housing markets. - Build models that reflect reality. - Turn data into a coherent story. - Create structure and repeatability. - Contribute to new analytical capabilities. This role operates in an extremely fast‑paced environment. The ideal candidate is comfortable producing high-quality economic work under time pressure, making pragmatic tradeoffs, and iterating quickly without losing methodological discipline. Qualifications - Strong foundation in Economics (Master’s or PhD preferred). - Advanced proficiency in time series econometrics (ARIMA, VAR, GARCH, State-Space models, etc.). - Ability to structure, organize, and document large-scale coding projects (Python/R, SQL). - Ability to articulate a clear thesis and explain the "Why" behind the forecast. - Experience building models that live in a research or production environment. Requirements - Strong foundation in Economics. - Advanced proficiency in time series econometrics. - Technical execution in coding (Python/R, SQL). - Industry intuition and ability to articulate forecasts. - Production experience with models. Benefits - Meaningful work and opportunities for career growth. - Competitive Salary. - Comprehensive benefit package (Medical, Dental, Vision). - 100% Company paid Life Insurance, Long Term Disability, and Short-Term Disability coverage. - 401k with company match. - Paid vacation and general holidays. - Employee Assistance Program (EAP). - Paid Volunteer Day. - Live Meditation Sessions. - Employee Recognition Platform. - Virtual Wellness Program. - 100% Hybrid – and always will be! - Visionary Leadership Team.

Senior AI Data Scientist Your Mission as a Senior AI Data Scientist Energage is seeking a Senior AI Data Scientist to join our AI and Product Innovation team. This role is designed for an AI-native, product-minded data scientist — someone who works fluently in Python, thinks in terms of models, agents, and reasoning systems, and enjoys turning ambiguity into intelligent product capabilities. You will help shape the future of Employee Experience and Talent Management by building AI-driven Advisors, Assistants, and Analysts that help leaders understand their organizations, ask better questions, and take better action. You will drive the design and delivery of production-grade AI systems built on large language models, agentic workflows, retrieval-augmented generation (RAG), and knowledge graphs. This is not a pure AI engineering or infrastructure role — it is a hands-on, applied AI and data science role focused on reasoning, analytics, and decision support, with strong ownership from concept through production. Accountability and Impact: In this role, you'll... - Design and deliver AI-powered advisors, assistants, and analytic agents that reason over organizational data, context, and knowledge to support real workplace decisions. - Build and maintain high-quality, production-ready Python services that power AI applications and backend services that integrate into Energage’s platform. - Apply, adapt, and fine-tune foundation models (OpenAI, Gemini, Claude, etc.) to deliver reliable, context-aware, and explainable AI experiences. - Architect agentic AI systems that coordinate reasoning, planning, and tool use using frameworks such as CrewAI, LangChain, Autogen, or similar. - Design and evolve RAG pipelines and knowledge-based approaches, enabling AI systems to ground responses in organizational data and domain expertise. - Develop and systematically test prompting strategies, agent behaviors, and interaction patterns to optimize accuracy, robustness, and user trust. - Enable conversational analytics, allowing users to explore data, generate insights, and answer complex questions through natural language. - Partner closely with product managers, engineers, and researchers to move AI Capabilities from prototype to scalable, production-ready features. - Stay current with emerging trends in Generative AI and Agentic AI, translating emerging techniques into practical product innovation. - Clearly communicate AI concepts, tradeoffs, and insights to both technical and non-technical stakeholders. What Success Could Look Like (First 6–12 Months) - One or more AI advisors or analytic agents you’ve designed are in production and actively used by customers. - AI outputs are demonstrably grounded in data and trusted by users. - Prompting, evaluation, and agent patterns you’ve established become reusable standards across the team. - Product and engineering partners rely on you as a thought partner for AI-driven decision support. - You help raise the overall bar for applied AI quality, safety, and clarity at Energage. What You Will Bring to the Role Required Qualifications - 5+ years of experience in applied AI, data science, or machine learning, with meaningful hands-on work in generative AI. - Strong Python expertise, with experience building data-centric or AI-driven services used in production environments. - Practical experience working with LLM APIs (OpenAI, Anthropic Claude, Gemini, etc.). - Deep skill in prompt engineering, including structured prompt design, evaluation, and iteration for complex, multi-step reasoning tasks. - Solid understanding of agentic AI concepts, such as multi-agent coordination, planning, tool invocation, and memory. - Experience designing and implementing RAG architectures, including vector search and knowledge-grounded reasoning. - Familiarity with AI agent frameworks such as CrewAI, LangChain, Autogen, or similar tools. - Track record of delivering production-quality AI solutions, including testing, monitoring, and iterative improvement. - Strong communication skills and the ability to explain AI behavior, limitations, and outcomes clearly. - Comfort operating in ambiguous, early-stage problem spaces, with curiosity and a strong sense of ownership. Preferred Qualifications - Experience embedding AI into SaaS or enterprise products, especially user-facing, decision-support systems. - Hands-on experience designing or implementing MCP servers to expose tools, data, or workflows for agentic systems. - Experience using AI to interrogate data, generate insights, and support analytical reasoning via natural language interfaces. - Familiarity with vector databases and semantic search technologies (e.g., Pinecone, Weaviate, Chroma). - Experience supporting AI-driven insights with analytics pipelines or data visualization. - Working knowledge of cloud platforms (AWS, GCP, Azure) and containerized deployment (Docker, Kubernetes), without a focus on heavy infrastructure ownership. - Interest or background in HR Tech, people science, employee experience, or organizational analytics. Compensation and Benefits: This position has a salary range of $175,000 to $195,000 annually based on relevant experience. This role is also company bonus eligible. In addition to base pay, our total rewards package includes: - PTO policy includes company holidays, sick time, vacation time, and floating holidays - Remote - Company pays a portion of individual health care premium - Option to participate in a company-sponsored 401(k) - Training and education - Professional development; all employees have access to a third party professional coach - Tuition reimbursement program - Opportunity to work for a purpose-driven organization using business as a force for good (https://www.bcorporation.net/) Energage is a remote workplace with employees in various US locations. While our employees enjoy the flexibility of daily remote work, they are also given the occasional opportunity for in person interaction. This includes in our office in Exton Pa, or in a coworking space/out in their local area. This role is available for remote work in the following states: - Arizona - Delaware - Florida - Georgia - Maryland - Michigan - North Carolina - Nebraska - New Jersey - New York STATE (NYC residents excluded) - Pennsylvania - South Carolina - Tennessee - Texas - Wisconsin If you reside outside of the above locations, you will not be considered for this role. About Energage: Energage is a purpose-driven company that helps organizations turn employee feedback into useful business intelligence and credible employer recognition through Top Workplaces. Built on 19 years of culture research and the results from 23 million employees surveyed across more than 70,000 organizations, Energage delivers the most accurate competitive benchmark available. With access to a unique combination of patented analytic tools and expert guidance, Energage customers lead the competition with an engaged workforce and an opportunity to gain recognition for their people-first approach to culture. For more information or to nominate your organization, visit energage.com or topworkplaces.com. Energage is committed to fostering a diverse and inclusive environment. We are proud to be an equal opportunity employer. Energage encourages all qualified candidates to apply, including those of any race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

• Stay current with the latest LLM research, architectures, and advancements in the field including real-time models and multimodal systems. • Identify and define approaches for complex AI challenges leveraging state-of-the-art LLMs. • Write clean, maintainable, production-quality code following software engineering best practices and design patterns. • Design rigorous experiments to test hypotheses and validate model performance. • Conduct thorough code reviews and maintain high code quality standards.

• Lead, mentor, and manage a team of data scientists — setting expectations, giving feedback, and building people up. • Own execution quality for data science delivery, ensuring research translates into production-ready, well-documented systems. • Partner with Product to define research priorities and with Engineering to ensure models integrate cleanly into production. • Step into complex modeling and research efforts yourself when senior technical judgment and experience are required. • Build and improve the team’s processes — including experimentation standards, methodology reviews, documentation practices, and model handoff workflows.