Engine No. 1 is investment firm purpose-built to lead the next generation of investing. We believe that creating value for shareholders cannot be separated from the impact companies have on their stakeholders. We also believe that a company’s performance is greatly enhanced by the investments it makes in workers, communities, and the environment. The firm intends to invest as an active, engaged owner in both public and private companies, with a focus to generate economic value over the long-term through four business lines: private equity/early investor, concentrated long/short funds, impact investment through activism campaigns and ETFs.
Founded by a seasoned team of industry leaders, we are seeking enthusiastic and engaged professionals to join us to help achieve the firm’s mission and help lead the movement towards more sustainable and inclusive capitalism.
The Data Scientists at Engine No. 1 combine quantitative research with data science software development. The position can be located in San Francisco or NY.
The Data Scientist’s top priority is to focus on both investment returns and impact together and not as conciliatory or opposing forces. The DS will identify, procure, and integrate both traditional data and ESG data from multiple sources and combine that data with relevant financial information to derive investable insights and ultimately generate alpha for the firm.
The candidate will also be expected to use the combined data set to conduct research and build models that relate ESG and financial data. The DS will be responsible for identifying and evaluating new data sets (structured and unstructured) from disparate sources that relate to public companies’ environmental, social, economic, and political impacts.
- Support Senior Data Scientists in all functions necessary to perform their responsibilities
- Identify timely and unique data sets, ensure data relevance and quality through appropriate selection of data sources, sound collection, data quality tests.
- Manage large amounts of complex data and run quantitative queries.
- Build statistical and financial models that distill ESG and financial data into actionable insights.
- Perform regular reviews of academic literature on ESG investing, and relevant ESG topics and communicate to the team findings and/or empirical developments.
- Use ML, statistics, and experiments to scientifically prove hypotheses.
- Work alongside leadership and engineering managers to create the Modeling Engine platform.
- Create insights, reports, and analytics that support Engine No. 1 lines of business using a combination of open source and third-party analytics.
- Collaborate with academic experts and attend seminars to stay up to date in the latest advancements of Machine Learning in Asset Management.
The successful candidate will have a deep interest in solving complex problems, possess a strong desire for excellence, and maintain an active desire to learn. Additionally, the DSE will have:
- Proficiency with statistical and data analysis including but not limited to Bayesian methods and programming tools such as Python, R, SQL or Matlab.
- Data visualization with Tableau/Lookr or Python to create accessibility to products.
- Experience with cloud computing resources
- Ability to clearly communicate quantitative and fundamental concepts verbally and in writing to internal audiences, as well as clients and prospects.
- An advanced degree in a quantitative field such as Computer Science, Quantitative Finance, Statistics, Engineering, Applied Mathematics, or Physics is strongly preferred and highly valued.
- 5-7 years of experience in a relevant field researching real-world data problems (preferably in investment management or finance) with quantitative research or data science.
- Experience evaluating and testing trading and back-testing portfolio strategies.
- Prior exposure to ESG analysis and familiarity with ESG data vendors is preferred.
- Passionate about reinforcing positive social and environmental impacts at scale through a new approach to investing.
Engine No. 1 is an Equal Opportunity Employer.