Head of Data Science and Analytics - SVB Capital Head of Data Science and Analytics - SVB Capital …

Silicon Valley Bank
in Menlo Park, CA, United States
Permanent, Full time
Be the first to apply
Competitive
Silicon Valley Bank
in Menlo Park, CA, United States
Permanent, Full time
Be the first to apply
Competitive
Head of Data Science and Analytics - SVB Capital
This hire will be the leader of all of SVB Capital's data science and analytics initiatives, including setting a strategy, vision, and roadmap to create a data-driven investment decision-making culture. This individual will manage a team of data professionals to support the group's investment activity. The Head will also serve as an ambassador to internal executives and teams as well as external limited partners, fund managers, and other constituents.
  • People Management - Retain, recruit, and develop a team of high-performing data professionals, including mentorship, career pathing, development planning, and organizational design
  • Thought Leadership - Serve as an ambassador to communicate our data-driven strategy as a competitive advantage, including presenting to limited partners, communicating with internal leaders and external constituents, building a network of data scientists, etc.
  • Product Management and Engineering - Design, build and roll out new data/analytics tools and "products" to internal and external audiences. Oversee all of the engineering efforts for the team, including front-end development, back-end development, and database management tasks.
  • Investment Analytics and Insights - Oversee and perform data-driven analyses to create actionable insights and support the sourcing, due diligence, portfolio monitoring, and market research initiatives of the group
  • Data Science - Implement advanced data science techniques and predictive analytics models using SVB and SVB Capital's proprietary and external datasets
  • Data Operations/Infrastructure - In collaboration with SVB's data management efforts, oversee data operations, including the processing of unstructured data (which involves managing multiple vendor relationships), managing external data sets, building ETL procedures, and mapping/cleaning data

This individual will collaborate with SVB Capital leadership to set strategy, determine optimal team structure, hire new team members, and develop a product roadmap.

Qualifications
  • Venture capital industry knowledge
  • Basic understanding of venture funds, company cap tables and investment terms
  • Familiarity with SVB's banking platform, product set, and client base
  • Excellent communication skills (verbal, written, listening)
  • Strong leadership and project management skills
  • Database Skills: very comfortable working with relational databases (SQL), experience building ETLs, proficient in Microsoft Excel
  • Programming Skills: comfortable with many (not necessarily all) of the following programming languages/frameworks - Python (Django, Flask), Node.js (Express), PHP (Laravel), HTML, CSS (Bootstrap), Javascript (React, Angular, Vue)
  • Data Visualization/Business Intelligence: Comfortable with Tableau, Power BI, and D3.js
  • Data Science: Comfortable with tools such as pandas, R, Julia, MATLAB, TensorFlow, or any other statistical software
  • Other: Comfortable working with Git/GIthub, Docker, AWS, Figma/Sketch/InVision, and other developer tools
  • Ability to lead a team of high-performing engineers/data scientists/analytics professionals
  • Ability to understand both business and technical requirements
  • Highly collaborative work style, including ability to partner with broader SVB Data Management and Analytics functions
  • Ability to collaborate with leadership and cross-function teams
  • Ability to communicate with senior executives and clients
  • Ability to work with large datasets
  • Ability to implement advanced data science techniques and models
  • Ability to work in a fast-paced, dynamic environment
  • Bachelor's Degree or equivalent is required, preferably in Computer Science, Engineering or other quantitative disciplines
  • 10+ years of relevant experience in a product/engineering/data science role - experience building products individually AND leading a product/engineering team
  • Advanced degree desirable, in technical fields or MBA/other management disciplines
  • Experience/exposure to venture capital industry, preferably at a venture firm or venture-backed startup


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