• Location: New York NY
• Type: Perm
• Job #23301

A global private markets fund with over $60b AUM is looking to hire a Head of Data Science and Engineering.  The team is responsible for defining the data strategy and architecture for the firm, as well as designing and implementing data pipelines, data lakes, analytical dashboards, predictive models, machine learning algorithms, and data science applications.

Responsibilities:
–    Partner with leaders from Technology, Transformation Office, Investment Team & Portfolio Management and Investor Relations groups to refine and execute on the firm’s data science strategy 
–    Research and apply best practices and methodologies in data science for private markets investment firms, such as machine learning, artificial intelligence, or deep learning.
–    Stay updated on private markets industry trends, regulatory needs, software vendor offerings, and investment team feedback to guide product decisions and maintain Pantheon’s competitive edge
–    Develop market-leading uses cases for data science applications and predictive models to support Pantheon’s investment and risk professionals
–    Align our data strategy with firm priorities, establish the data sources, identify the tools needed, and oversee data governance and quality standards

Qualifications:
–    Bachelor’s degree in Engineering, Technology, Data Science or a related field; an advanced degree is preferred
–    Minimum of 10 years of relevant experience, with significant expertise in data engineering, data science, machine learning, natural language processing fields within investment firms
–    Track record of working with and organizing data within financial services, asset management, private markets
–    Proficient with data lake concepts and tools such as Azure Databricks or Snowflake, metadata management principles, and data governance best practices
–    Proficient in programming languages, such as Python, R, or SQL; frameworks, such as Teraform, TensorFlow, PyTorch Keras, HuggingFace & Langhain or Spark, analytics tools such as Azure Synapse, and reporting platforms such as PowerBI & Tableau
–    Proficiency in managing processes involving acquiring, storing, processing and delivering structured and unstructured data for analytical applications  
–    Demonstrated expertise in data governance, data quality management, and the implementation of analytics platforms