# A startup: Quantitative Modeler [Remote, US]

A Startup is seeking a talented and highly motivated Quantitative Modeler for a unique and exciting opportunity with a small team looking to accurately predict the events (team and player level) of future sports competitions.

**At: a startup**

**Location: Remote (US)**

**Position: Quantitative Modeler**

**This position has been filled.**

Looking for a talented and highly motivated Quantitative Modeler for a unique and exciting opportunity with a small team looking to accurately predict the events (team and player level) of future sports competitions. Candidate should have hands-on experience in traditional data science (analyzing data) and more modern data science (AI, deep learning). Degree in a relevant scientific field required (mathematics, statistics, data science, actuarial sciences, etc.). Candidates should have a high level of enthusiasm toward sports analytics and prediction of future outcomes in the sports world. Candidates should be capable of working in a remote environment.

**Required Qualifications: **

- Python (scripting, numpy, scipy, matplotlib, scikit-learn, jupyter notebooks)
- Tensorflow or equivalent deep learning framework such as PyTorch, Caffe(2), MXNet
- Experience with machine learning algorithms, such as neural networks/deep learning, SVM, Random Forest, generalized linear models, etc.
- Experience with Financial Market Analysis (Trading systems, investment analysis, Hedging, high frequency trading, etc.)

**Desired Qualifications: **

- R, MATLAB, SAS, mongoDB, SQL Server
- Sports Analytics
- Experience with Database Management
- Background in Game Theory, Control Theory

**Candidates will be considered if any of the following apply:**

- BS degree with 3+ years of experience in analytics
- MS graduates with focus in analytics
- Outstanding experience in sports analytics

**Job Description**

- Investigate, identify, develop and optimize new methods, algorithms and technologies to derive novel, competitive insights from disparate data sources.
- Collaborate with other data scientists and developers to identify, design, build and maintain tools, analytical workflows and applications to streamline and strengthen current processes.
- Applying new and emerging analytical methods and visualization technologies on real world data for the purposes of building investment strategies around the outcomes of sporting events.