Quantitative Researcher - Private Markets - Stealth Fintech company

Opportunity Overview: 

Are you passionate about leveraging the power of machine learning and artificial intelligence to revolutionize the world of venture capital investing? Join our dynamic and ambitious early stage fintech company as a quantitative researcher. In this role, you will have the opportunity to leverage the data in the venture capital space to build and deploy cutting-edge predictive models that will shape investment decisions, optimize portfolio management strategies, and drive our overall performance. Be at the forefront of innovation, work with a cross-functional team of experts, and contribute to the growth of a company poised to transform the fintech industry. If you're ready to make an impact and be part of an exciting journey, apply now and unleash your potential in this thrilling opportunity!

Job Summary:

We are an early stage fintech company dedicated to revolutionizing the world of venture capital investing. We are seeking a talented and passionate Quantitative Researcher to join our team and develop cutting-edge predictive models for venture capital outcomes. As a specialist in this field, you will play a crucial role in helping us make data-driven investment decisions, enhance portfolio management strategies, and optimize our overall performance.

Responsibilities:

1. Develop and implement state-of-the-art machine learning and artificial intelligence models to predict venture capital outcomes, including success rates, return on investment, and exit strategies.


2. Collect, clean, and preprocess large datasets related to venture capital investments, including historical investment data, market trends, financial indicators, and company-specific information.


3. Collaborate with cross-functional teams, including investment analysts and credit specialists, to gather requirements, define model objectives, and integrate the predictive models into our lending decision-making processes.


4. Utilize statistical techniques and machine learning algorithms to analyze complex data patterns, identify relevant features, and build accurate predictive models.


5. Continuously research and apply the latest advancements in machine learning and artificial intelligence techniques, as well as industry best practices, to ensure the models are state-of-the-art.


6. Evaluate and validate the performance of the developed models using appropriate metrics and statistical methods and iterate on model improvements based on feedback and results.


7. Present findings, insights, and model outputs to both technical and non-technical stakeholders, effectively communicating the value and implications of the predictive models.


8. Collaborate with the data engineering team to optimize data pipelines and ensure efficient data processing and model training.


9. Maintain documentation of the developed models, including methodologies, assumptions, and limitations, to facilitate transparency and reproducibility.


10. Contribute to the development of a data-driven culture within the company by sharing knowledge, providing mentorship, and promoting the use of machine learning techniques across different departments.

Qualifications:

1. Graduate degree in physics, statistics, mathematics, computer science, or a related field.


2. 3 – 5 years’ experience as a Quant, ML Engineer, Data Scientist, or similar role in the financial or investment industry.


3. Strong knowledge of machine learning techniques, including regression, classification, clustering, and deep learning algorithms.


4. Proficiency in programming languages such as Python, R, or Scala, along with experience using popular machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).


5. Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.


6. Experience working with large datasets, data manipulation, and database querying languages (e.g., SQL).


7. Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and distributed computing frameworks (e.g., Hadoop, Spark) is a plus.


8. Excellent problem-solving skills and the ability to think analytically and critically.


9. Strong communication and presentation skills, with the ability to convey complex concepts to both technical and non-technical audiences.


10. Self-motivated and detail-oriented, with a passion for innovation and a strong desire to contribute to the growth of an early stage fintech company.

Join our dynamic and ambitious team, where you will have the opportunity to shape the future of venture capital investing through the power of machine learning and artificial intelligence. Apply today!

Candidates need to be legally authorized to work in the United States. We are not able to sponsor visas currently. Preference will be given to candidates who are local to Santa Monica or willing to relocate. Relocation assistance is available for this role. Remote work considered for the right candidate.