Data Scientist Position Available In New York, New York
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Job Description
The Data Scientist (multiple openings) at MPG Operations LLC in New York, NY will join a commodities investment team to explore, analyze, and harness a large variety of structured and unstructured datasets. Build datacentric solutions to inform the team’s investment process. Communicate sophisticated statistical and technical techniques in simple language. Analyze, manage, and store vast amounts of datasets from market to alternative data vendors. Communicate and provide data insights to investment teams (portfolio managers and analysts). Mine new alternative datasets to uncover signals and determine value. Write code to tag, clean, and normalize large unstructured and structured datasets. Backtest datasets to assess their correlation to company Key Performance Indicators (KPIs). Work alongside the data sourcing team to identify new potential data products and vendors. Develop data analysis tooling and libraries alongside the rest of the data science team. Construct visualization dashboards to present key insights. This position may involve work at unanticipated Millennium locations in the United States.
Salary:
$150,000 to $200,000 per year.
Requires a Master’s degree in Mathematics, or a related quantitative field, plus 3 years of experience in a financial data science, or related, occupation. Must include 3 years of experience with each of the following: (1) structured and unstructured datasets; (2) soft commodities modeling; (3) machine learning; (4) ETL processes, including running and managing pipelines using Airflow; (5) AWS, Docker, Python, and scikitlearn; (6) create model monitoring dashboards in Databricks; (7) JIRA; (8) Regression modeling, Time Series, and Deep Learning; (9) climate modeling; (10) write SQL queries; and (11) company fundamental financial metrics.
To apply please send resume to recruiting@mlp.com and reference job code “0644” when applying.#LI-NDI #LI-DNI #
LI-DNPMinimum Salary:
150,000
Maximum Salary:
200,000
Salary Unit:
Yearly
