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Principal Applied Scientist – Time Series Forecasting
Company background
Keystone.ai is a global technology and services firm specializing in enterprise AI, economics advisory and technology strategy. Keystone’s Deep Enterprise™ AI platform—built by AI/ML industry pioneers—helps large enterprises optimize business decisions at scale. By combining advanced technology, strategic consulting, and applied econometrics, Keystone delivers innovative solutions to organizations across the technology, business, legal, and government sectors. Founded in 2003, Keystone operates globally with offices in New York, San Francisco, Boston, Seattle, London, and Dubai.Position Overview
We are seeking a Principal Applied Scientist who will serve as a thought leader and drive the development of our foundational forecasting capabilities - Keystone’s flagship product for advanced time series forecasting and intelligent inventory management. Our team builds sophisticated forecasting solutions deployed across diverse industries, helping clients transform critical business processes, reduce waste, and modernize operations through data-driven insights and predictive modeling.In this role, you will lead other scientists and ML engineers, shaping the design, development, and deployment of robust forecasting models leveraging fundamental economic and structural time series techniques. You will use your extensive experience in econometric modeling, statistical forecasting methods, and applied time series analysis to produce innovative, industry-leading solutions that optimize supply chain and operational workflows.
If you are passionate about pushing the boundaries of forecasting methods, mentoring high-performing teams, and collaborating closely with business and technical stakeholders to deliver practical, impactful solutions, we invite you to apply. While deep expertise in deep learning techniques is not required, familiarity or exposure to such methods for time series forecasting is a plus.
What You’ll Do
- Provide Thought Leadership: Steer the strategy and vision for Keystone.AI by championing rigorous and innovative approaches in econometric and structural time series forecasting, supply chain optimization, and inventory management.
- Lead & Mentor: Provide technical leadership and mentoring to a multidisciplinary team of data scientists, economists, and ML engineers, guiding model development, methodological best practices, and impactful project delivery.
- Develop Advanced Forecasting Models: Design and refine statistical, econometric, and structural forecasting methods to accurately predict demand, optimize inventory, and derive actionable insights from complex datasets across diverse industries.
- Collaborate Cross-Functionally: Partner closely with product managers, economists, deep learning scientists, software engineers, and ML engineers to create scalable, practical, and end-to-end forecasting solutions that address real business challenges.
- Drive Innovation: Continuously enhance Keystone’s foundational forecasting capabilities by exploring new methods, frameworks, and modeling approaches, ensuring our solutions remain cutting-edge and impactful.
- Champion Operational Excellence: Ensure forecasting models are robust, interpretable, efficient, and production-ready, accelerating the deployment of forecasting solutions into real-world applications.
This role is based in Bellevue, WA or NYC with a flexible and hybrid work environment.
Basic Qualifications
- PhD in Economics, Statistics, Computer Science, Operations Research, or a related quantitative field.
- 10+ years of professional experience in applied time series forecasting, econometric modeling, structural economic analysis, or statistical modeling in practical business applications.
- Demonstrated experience applying fundamental economic, statistical, and structural time series modeling techniques, with a proven track record of developing and deploying robust forecasting models in production.
- Proven ability to lead and mentor teams consisting of economists, data scientists, and ML engineers.
- Excellent communication skills, capable of conveying complex technical concepts clearly to both technical and non-technical stakeholders, including executive-level audiences.
Preferred Qualifications
- Familiarity with deep learning methods for time series forecasting, supply chain optimization, or related domains.
- Experience incorporating economic theory and structural modeling into predictive models for supply chain and inventory optimization.
- Track record of successfully developing and operationalizing scalable forecasting systems in complex, enterprise-scale environments.
- Entrepreneurial mindset with a desire to work in a dynamic, self-directed, and innovation-focused environment.
US Salary Range: $195,000 - $308,000, plus an annual discretionary bonus, 401k contribution, and competitive benefits package. Actual compensation within the range will depend upon the level the individual is hired at based on their skills, experience, and qualifications.
At Keystone we believe diversity matters. At every level of our firm, we seek to advance and promote diversity, foster an inclusive culture, and ensure our colleagues have a deep sense of respect and belonging. If you are interested in growing your career with colleagues from varied backgrounds and cultures, consider Keystone Strategy.
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