Dir Data and Projects
Description
Title: Dir Data and Projects
Employer: Alvarez & Marsal Private Equity Performance Improvement Group LLC
Location: New York, NY
Salary Range: $151,000 - $225,000
Job Description:
Ensure projects adhere to budget, schedule and scope. Oversee bespoke client projects from inception through delivery, managing expectations, project timelines, and ensuring superior outcomes. Serve as liaison between teams and clients to help transform how open source and alternative data is used for A&M clients. Collaborate closely with technical teams to define and refine requirements, particularly for complex processes such as entity resolution, integration workflows, and feature engineering. Ensure consistent alignment between project strategies and the overall product roadmap. Interact with clients and translate their needs into deal idea generation dashboards and other value add products. Actively participate in weekly product and data roadmap sessions and sprint planning, providing guidance, timelines, and implementation risks. Provide input to vendor expenses, forecasting specifically related to data acquisition, and resource allocation. Conduct quarterly competitive analyses and market evaluations within the client data landscape, ensuring the practice consistently leads to data comprehensiveness, innovation, and relevance. Serve as a key liaison, clearly communicating strategic objectives, KPIs, and project performance expectations. Support go-to-market activities by contributing to data driven strategies and producing insightful analysis tailored to prospective client needs and market trends.
Minimum Requirements:
Bachelor’s degree or foreign equivalent in Management Info Systems, IT, or Business Administration, and minimum five years of experience in any occupation involving leading IT projects or data related initiatives. Must have experience with the following: performing data cleaning and analysis using advanced functions to create client ready reports; using SQL to visualize performance, metrics and answer data related questions to internal stakeholders; identifying and specifying string match patterns using RegEx; using SQL to extract and manipulate data to filter, join, aggregate, and clean datasets as well as perform data quality checks; using DBeaver or Redash to perform exploratory data analysis and create linkage between multiple tables; and Public data source experience with government filings such as SEC Form D, and similar datasets from U.S. federal agencies, used to extract relevant data points.
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