Job Title: Data Scientist / Machine Learning Engineer (Analyst, Associate)
Department: Labs
Work Location: Chicago
Reports To: Head of Labs
Who We Are:
Valor Equity Partners is a different kind of private investment firm. We invest in technology and technology-enabled companies that innovate and disrupt existing industries — from biosciences to transportation to food to health and wellness.
Our mission is to invest in and work side by side with companies that make the world a better place. These companies include SpaceX, Anduril, GoPuff, HackerOne, Cloud9, and others. We’ve had the honor of serving some of the world’s greatest entrepreneurs and companies.
Our values are core to all we do. These values are excellence, humility, integrity, and responsibility.
Valor means that we:
- Strive for excellence in everything we do;
- Maintain our humility and mutual respect no matter what circumstances we encounter;
- Insist upon the highest level of integrity in our interactions and in the logic of our investment process; and
- Demonstrate responsibility and dedication to all of our constituents.
About the Team:
Labs is an internal team at Valor that builds software to support the Firm’s investment process. It comprises software, data, and machine learning engineers as well as data scientists with diverse backgrounds and levels of experience. The team’s mission is to build cutting edge software applications and data models that generate proprietary investment insights and provide the investment team with tools that augment the investment decision making process.
About the Role:
- Develop features and machine learning models that augment the Firm’s investment decision making process
- Work collaboratively with machine learning engineers and software engineers to build, deploy, monitor, and maintain machine learning models
- Work collaboratively with team members to promote technical rigor and adopt best practices
- Collaborate with data scientists, engineers, and other stakeholders in translating project requirements into technical specifications
- You will help shape the future of software engineering at Valor by bringing your ideas on improving and automating what we do and how we do it
We’re excited about candidates that have:
- B.S. and/or M.S. in Computer Science, Applied Mathematics, Statistics, or related field, especially with coursework in machine learning
- 2+ years of machine learning, data science, and/or statistical modeling experience, with significant contributions that you can talk to
- Exceptional coding skills in Python and SQL, to include common Python libraries like Pandas, Scikit-Learn, PyTorch, and/or TensorFlow
- Experience with any of the following:
- Time-series modeling
- Graph-based modeling
- Supervised learning, especially boosted tree algorithms such as XGBoost and LightGBM
- Natural Language Processing (incl. LLMs)
Additionally, experience with any of the following is a bonus:
- Experience with deploying and monitoring machine learning models
- Experience with Docker and GPU-based infrastructure
- Experience with modern cloud platforms (AWS, Azure, or GCP)
- Modern data pipeline experience
- Big Data processing (Spark, PySpark, Scala, Dask)
- Passion for machine learning while being mission-driven, hard-working, humble, intellectually curious, and most importantly, great team players
- Bias for execution and delivery. You know that what matters is delivering software that works every time
- Ability to assist in system design and the generation of key technical assumptions while encouraging solutions that respect existing infrastructure
- Willingness to be resourceful, flexible, and adaptable; no task is too big or too small
Our Tech Stack:
- Frontend: React with Hooks, Material UI
- Backend: Python, Fast API
- Tooling: Google Cloud Platform
- Data: PostgreSQL, Firestore, BigQuery, Elastic Search, Prefect, Kafka, Scala, Spark, dbt
