A leading investment management firm is looking for a Data Scientist/Data Hunter to identify, source, and analyze alternative data forms which may include (surveys, point of sales, credit card data, geospatial. weather, shipping, USDA) and web harvested information and other forms of new, structured and unstructured information that will uncover actionable investment insights. This role is highly collaborative, working closely with credit analysts, portfolio managers, and traders to deliver innovative, data-driven insights that enhance the firm’s investment approach.

Key Responsibilities:

Collaborate with the investment team to support their analytical needs and provide actionable data-driven insights.
Drive platform advancements and innovation to improve the investment process.
Leverage large datasets, including public, paid, and web-scraped data sources, to support the credit team’s research.
Automate repetitive tasks to improve efficiency and streamline workflows.
Provide comprehensive data insights across all sectors and deliver findings to internal and external stakeholders.
Apply statistical and machine learning techniques for data analysis, backtesting, and uncovering correlations.
Utilize APIs to extract, integrate, and manipulate data efficiently.
Present complex data findings effectively to internal teams, clients, and potential clients.

Required Skills & Qualifications:

Technical Proficiency: Expertise in R, Python, SQL, and Snowflake.
Data Expertise: Strong experience with large datasets, data manipulation, web scraping, artificial intelligence, natural language processing, and automation.
Analytical Ability: Proven ability to apply statistical and machine learning techniques to solve complex problems.
Communication Skills: Excellent ability to present findings clearly to technical and non-technical audiences.
Financial Understanding: Awareness of the financial implications of data analysis, beyond just technical execution.
Education: A background in Data/Computer Science, Finance, or Accounting, or the firm would look at a candidate with relevant experience without a college degree.

Preferred Qualifications:

Solid understanding of finance, accounting, credit, and derivatives, including financial statements, credit risk assessment, and using derivatives for hedging and investment purposes.
Proven experience tailoring complex data presentations for various audiences, including clients and potential clients.
3–5 years of professional experience in data science or a related role, preferably in a financial or investment context.

Job Advantages:

A collaborative and dynamic work environment.
Opportunities to innovate and make a significant impact on investment decisions.
Competitive compensation and benefits package.

Keywords: High Yield Bonds, Alternative Data, Unstructured Data, Machine Learning, Business Intelligence, Text Mining, Data Scientist, Web Scraping, SQL, Parsing, Python, Scripting, Data Analyst

Please send resumes to Jim Geiger jeg@analyticrecruiting.com

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