MSCI, Inc. Seeks Senior Associate, Real Assets Data in New York, NY to: lead data scientist in the real estate data team. Build ML models and dashboards to help automate data ingestion and publishing.Utilize tools such as data bricks, python, github, R, PowerBI, Tableau. Collaborate with cross-functional teams, including product managers, engineers, and business analysts, to develop data-driven solutions that address complex business problems and drive investment decision-making in the commercial real estate industry (CRE). Lead the build and production of a chained hedonic structured time series model to better depict market cap rates and pricing metrics in CRE for clients who have used it to benchmark investments. Build the US multifamily liquidity scores model using R and Tableau to understand and quantify capital flows and liquidity in the US market. Use R and Python to build an unsupervised learning records exclusion model, and deployed it into production using Databricks, increasing efficiency by time saved from manual record processing. Lead the efforts to build and deploy a robust ML record linkage pipeline using geospatial, KNN, and string distance algorithms to automatically link CRE records from any unstructured datasets into the MSCI core database; Maintain dashboards for the performance of the Data Science team using Databricks and Tableau.SALARY & WORK SCHEDULE: $131,000 to $131,000/year, 40 hrs/wkREQUIREMENTS: Masterxe2x80x99s degree or foreign equivalent in Finance or a related field and three (3) years of experience in the job offered or related occupation: performing data analysis using Python and R, including Pandas, NumPy, and Scikit-learn; applying statistical techniques, including hypothesis testing, regression analysis, hypothesis testing and multivariate analysis; applying machine learning techniques, including regression, classification, clustering, random forest and ensemble methods; cleaning, transforming, and structuring large datasets using SQL, Python and R by writing complex SQL queries, data wrangling, and managing ETL processes; creating comprehensive dashboards and reports using Tableau and Power BI; utilizing cloud platforms including Amazon Web Services (AWS), Google Could Platform (GCP) and Azure for data science workflows including setting up cloud-based data storage and deploying machine learning models in a cloud environment; and working with big data processing frameworks including Hadoop, Spark, and Databricks. Telecommuting and/or working from home may be permissible pursuant to company policies. When not telecommuting, must report to work site.QUALIFIED APPLICANTS: Please e-mail your resume to: Ref: HA0423WEB. NO CALLS.EOE.What we offer you
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