— Senior Data Scientist
We are seeking an experienced and Senior Data Scientist with excellent analytical, communication and modeling skills to develop sophisticated models for equity investments to join our dynamic and innovative team.
This is a great opportunity for an ambitious data scientist to apply their depth of knowledge and experience toward building sophisticated machine learning models in finance.
More in Q&A.
What are we doing?
We are a fast moving investment firm utilizing the latest machine learning techniques to sift through terabytes of data to develop real world models that generate money for our clients.
Our work is fueled by our mission to invest in a future where the smart working people and best technology win and we believe that the investing process can be transformed with the scientific method.
Responsibilities:
- Work closely with a small but very capable and motivated team of data scientists, engineers and portfolio managers.
- Maintain code used in research and ensure results used in reports are reproducible by others on the team.
- Understand high level business objectives set by the HQ and deliver research results according to priorities set by the team.
- Consistently deliver high-quality insights on time and within budget.
- Provide ongoing feedback to the HQ, help maximize value derived from investments in research projects.
Requirements:
- Extensive education in mathematics, statistics, computational science, computer science or similar field (PhD is a plus but not required).
- 5+ years of professional hands-on data science experience.
- Mastery of modern data science software tools and practices (SQL, Numpy, Pandas, Scikit-learn, Jupyter Notebook).
- Hands-on familiarity with common software engineering practices and tools (Git and GitHub, pull requests and code reviews, unit and integration tests, continuous integration).
- Working knowledge of posix-like environments (Linux/macOS, Bash, SSH) and AWS (Athena, S3, Sagemaker, State Functions) are strongly preferred.
- Excellent verbal and written communication in English
In this role, many individual experiments are unsuccessful. That is OK and expected. We define success as::
a.) Carefully reasoning about what the next steps should be to test for improvements
b.) Coming up with an efficient means to test these next steps
c.) Execute those steps quickly using the resources we provide to do so
d.) Presenting those results without bias at our weekly discussion meetings
e.) Deciding (with the group) what the next experiments are; then back to step a
The right team member will:
a.) offer his thoughts
b.) listen to the deliberation of all the team members
c.) accept the ultimate decision of the executives based on feedback from the employee and others and work hard to implement that new direction
What else is important to us about this person?
We want someone with a passion for data science and machine learning who's had real practical experience on large data sets with many, many, many factors, and where there's a lot of noise and very low signal, who are able to kind of pull out the small bit of signal there is.
We are looking for team members that:
Understand the fundamentals of machine learning techniques, and gradient boosted trees specifically. We strongly prefer candidates to have had significant experience in real world situations applying sophisticated machine learning techniques to regression (not classification) based machine learning objectives over very large datasets.
Familiarity with boosted tree regression is an additional strong plus. It is quite easy to detect people who use buzzwords (or read up on ChatGPT) vs those who have really wrestled with problems of this sort.******
We're looking for somebody who can basically help build models and potentially do optimization with all that data and those signals.
Team size and structure
1 Director of Product, 1 CEO, 4 Data Scientists, 1 Software Engineer
Where are the people who make technical decisions on the project?
USA
How many stages of the interview, and with whom?
- Interview with a recruiter - 30-45 min.
- Director of Product - 45-60 min.
- Test assignment - 2-3 hours
- Technical interview with the team - 60min.
- FInal interview - 60 min
Additional details:
- Is there a test assignment? - Yes
- Is the interview in English? - Yes
- Salary range: $8-12k USD gross
- B2B form of employment