Open Position

Econometric Deep Learning Researcher

ML-Driven Econometric Forecasting Researcher

Part- or Full-time role

Do you love to work at the absolute cutting edge? Do you want to help make renewables more sustainable, and work in a rapidly-developing field? If you want to join a team where you can have a real impact on the development of the business, integrate your passion for advanced computing, and work in a dynamic environment, we want to hear from you!

About ForeQast 

At ForeQast we apply advanced classical and quantum computing to solve the world’s toughest challenges. We are dedicated to building simulations of complex real-world systems that allow our customers to continually benefit from advances in both quantum and classical hardware. Our top priority is to build forecasting and optimization tools on hybrid quantum-classical systems for industrials including utilities.

About the position:

ForeQast is seeking outstanding statistics and deep learning researcher for at least 6-month paid positions for both part- and full-time employment. It could turn to a full-time position if we work together well. You can be either a student or a professional, and we’ll pay you appropriately. You will be one of the key researchers for projects that focus on building and testing novel classical deep learning methods. You will work with other researchers in the group, and business people to bring use cases to production-ready code.

The goal of the collaboration is the development of an optimization and forecasting platform for our industrial clients, as well as publishing in high-impact journals. This project offers you an opportunity for getting hands-on experience in top-level industrially relevant research and development.

Key roles include:

  • Apply state-of-the-art time series and deep learning algorithms to forecasting data.
  • Design and build statistical and deep learning solutions for forecasting problems.
  • Provide technical feedback to support the team in how things should be built and deployed.
  • Advocate and implement the best practices to ensure the team is working effectively to deliver customer value while also constantly learning to remain up to date in a rapidly changing domain.
  • Identify, propose and implement new methods and opportunities for our clients that have tangible business impact.
  • Synthesize and apply relevant insights from academic literature on time series forecasting to our products.
  • Collaborate effectively with product management, engineering, and design teams to deliver products that have a quantifiable impact on the business.

Knowledge, skills, and abilities:

  • A degree in a related field (Data Science, Computer Science, Statistics, Econometrics, Mathematics, or a quantitative-related field) or equivalent professional experience. 
  • Experience with statistical methods in time series forecasting such as jump-diffusion models and state-of-the-art deep learning models for forecasting.
  • Proven track record working on forecasting and optimization projects in finance or utilities (at least as part of your gratuate studies).
  • Experience in performing quantitative analysis, and presenting those findings to technical and non-technical audiences.
  • Experience in manipulating and analyzing data.
  • Programming language: Python.
  • Experience with SQL, AWS is a plus.
  • Some familiarity with Monte Carlo methods is a plus.

ForeQast is an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

  • Seniority Level: Entry- to intermediate-level
  • Industry: Computer software
  • Employment Type: Paid part- or full-time
  • Job Functions: Algorithm development for power market forecasting
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