Data Analyst |
Remote, with time overlap between 6 AM – 11 AM Eastern US Time For our client who is hedge fund we are looking for an experienced and talented Data Analyst with excellent analytical, communication and data engineering skills to manage a sizable data pipeline for advanced equity analysis and portfolio investing. The employee will support a sophisticated quantitative investing team by maintaining and improving a large data pipeline that feeds thousands of features to models which automate investing decisions based on business fundamentals. Key Characteristics: ● Understand equity investing and fundamental analysis and the data that supports it ● Support a sophisticated data pipeline that flows data from various sources to several differentenvironments for different types of analysis ● Incorporate new sources of data with appropriate time series alignment to ensure proper dataexposure and prevent forward data leakage ● Extreme attention to detail and passion for digging deep into data quality and consistency froma business domainExcellent English communications skills are critical, especially around the data science, machine learning, and equity investing domains. ● This is an excellent opportunity for an ambitious Data Analyst to apply their depth of knowledge and experience toward managing and advancing a state of the art large data pipeline with significant financial impact. Responsibilities: 1. Understand high level business objectives (related to equity investing) set by the HQ and deliver data products according to priorities set by the team. 2. Work closely with a small but very capable and motivated team of data scientists, engineers and portfolio managers. 3. Maintain and advance a Tableau Business Intelligence Reporting infrastructure for purposes of reporting P&L, returns, exposure reports (sector, industry, risk factor, and others). 4. Support the various data science and machine learning teams 5. Lend development and operational support to the trading execution infrastructure. Requirements 1. Strong understanding of the DWH principals 2. Strong experience with Python, Snowflake (any other modern column database), Airflow, DBTand AWS (esp S3+Athena) 3. 5+ years of professional hands-on Data Analyst experience. 4. Experience with Business Intelligence tools (Tableau or similar BI tools) 5. Hands-on familiarity with common software engineering practices and tools (git and github, pullrequests and code reviews, unit and integration tests, continuous integration). 6. Excellent verbal and written communication in English (Russian is a plus). 7. Experience in the financial services industry – especially equity investing – is a strong plus. |