Senior Data Scientist

Senior Data Scientist

We are looking for an experienced and talented data scientist with excellentanalytical communication and modeling skills to develop sophisticated models forequity investments. Candidates must have strong experience with Python JupyterCatboost (or equivalent boosted regression tree modeling packages). Strong Englishand teamwork skills are crucial. We are looking for someone to lead the team andgrow it over time.

The employee will apply cuttingedge data science and machine learning tools toautomate investing decisions based on business fundamentals. Strong proficiency inmanaging complex data science projects endtoend is a must: Understand the business problem (fundamental equity analysis) Prepare data and develop models using advanced statistical and machine learningtechniques Make rapid incremental progress communicating effectively with meaningful andinsightful reports

Excellent English communication skills are critical especially around the datascience machine learning and equity investing domains. This is an excellentopportunity for an ambitious data scientist to apply their depth of knowledge andexperience toward building sophisticated machine learning models in finance.

Responsibilities:

1. Understand highlevel business objectives set by the HQ and deliver researchresults according to priorities set by the team.

2. Work closely with a small but very capable and motivated team of data scientistsengineers and portfolio managers.

3. Maintain code used in research and ensure results used in reports arereproducible by others on the team.

4. Consistently deliver highquality insights on time and within budget.

5. Provide ongoing feedback to the HQ helping maximize value derived frominvestments in research projects.

Requirements:

1. Extensive education in mathematics statistics computational science computerscience or a similar field (PhD is a plus but not required).

2. 5 years of professional handson data science experience.

3. Mastery of modern data science software tools and practices (SQL numpyPandas scikitlearn Jupyter notebooks).

4. Handson familiarity with common software engineering practices and tools (gitand GitHub pull requests and code reviews unit and integration tests continuousintegration).