Senior Data Scientist

1 week ago


Culver City, California, United States Spotter Full time

Overview:

Spotter, named one of TIME100's Most Influential Companies this year, empowers top YouTube creators to accelerate their business and unleash their full creative potential by giving them access to the capital, knowledge, and community they need to succeed at scale. As the top provider of creator-friendly growth capital, Spotter tailors our investments to meet the unique needs of each creator we partner with, giving them the freedom to create without compromise.

Creators are free to reinvest their funds however they choose, from hiring a team, to building their own production studios, and everything in between, all while maintaining total control over their catalogs, their channels, and their future earnings. In addition to funding, Spotter provides creators with in-depth data insights into the performance of their existing content, enabling them to leverage the full value of their library, as well as the value of future uploads and how they can improve performance in the future.

Featured in Forbes, Fast Company, Variety, Axios, and more, Spotter has already deployed over $850 million to YouTube creators to reinvest in themselves and accelerate their growth. Spotter has licensed content that consists of over 725,000 videos, which generate 88 billion monthly watch-time minutes. With our curated premium video catalog, we deliver a unique scaled media solution to Advertisers and Ad Agencies that is transparent, efficient, and 100% brand safe.


What You'll Do

As a Senior Data Scientist, you will play a critical role in strategic decisioning at Spotter. In addition, you will assist & grow into areas of strategic knowledge that will be key to maintaining and advancing the company's competitive advantage. You will be tightly integrated with the highest level of leadership in daily operational execution and long-term strategic knowledge development.

Responsibilities

  • Work with massive amounts of digital data (Web, App, API) and sophisticated tools in an industry leading Big Data environment.
  • Build everything from basic reports to advanced machine learning models and algos to help YouTube creators to grow from "creators" to "enterprises" with world class underwriting models and brand efficient media solutions to optimize media yield.
  • Maintain, optimize and innovate analytic models driving all insights and reporting
  • Provide visibility, unearth insights, and develop early indicators into the performance of licensed content
  • Conduct ad-hoc analysis to further enhance our understanding of content performance
  • Work with product team to revolutionize the product and services we offer with a data-driven approach
  • Collaborate with the engineering team to test, implement and deploy modeling solutions to production systems.
  • Partner with the sales team to optimize lead generation to help grow asset deployment targets
  • Partner with data engineers to ensure smooth, efficient, resilient, and agile knowledge delivery pipelines
  • Experience guiding strategic direction of workgroups, setting policy, while also having the skills to be an individual contributor
  • Support and train junior team members on tools and technical tasks to guide their learning while supporting the organizational analytic needs

Who You Are

  • Master or PhD in Data Science (preferred) or in a quantitative field (Computer Science, Engineering, Statistics, Mathematics, Physics, Operation Research etc.)
  • 10+ years experience with a Master's or 6+ years professional experience with a PhD
  • 1+ years team lead experience
  • Hands-on experience in building models using classic statistical modeling techniques and deep learning (LSTM, CNN, etc...)
  • Experience in data querying languages such as SQL, scripting/analytical languages such as Python/R.
  • Deep understanding of machine learning/statistical algorithms such as XGBoost
  • Demonstrated ability to frame business problems into mathematical programming problems, apply thought leadership and tools from other industries or academics to engineer a solution and deliver business insights.

Preferred

  • Large Language Model (LLM) experience (training, fine tuning, etc..)
  • Experience in large data processing and familiarity with big data platforms and applications such as Hadoop, Pig, Hive, Spark, AWS.
  • Financial industry backgrounds
  • Knowledge of the YouTube or Content Creator industry

Personal Attributes

  • Ability to understand and analyze data and communicate findings to stakeholders
  • High level of comfort with quantitative concepts
  • Strong attention to detail
  • Best-in-class analytical/critical/creative thinking skills
  • Innovative and flexible approach to collaboration and development
  • Ability to thrive in entrepreneurial environments with multiple projects and evolving priorities.
  • Work independently/remotely with little oversight
  • Forge relationships at all levels of the company

Why Spotter

  • Medical insurance covered up to 100%
  • Dental & vision insurance
  • 401(k) matching
  • Stock options
  • Autonomy and upward mobility
  • Diverse, equitable, and inclusive culture, where your voice matters.

Spotter is an equal opportunity employer. Spotter does not discriminate in employment on the basis of race, religion, creed, color, national origin, ancestry, citizenship, physical or mental disability, medical condition, genetic characteristics or information, marital status, sex (including pregnancy, childbirth, breastfeeding, and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, military status, veteran status, use of or request for family or medical leave, political affiliation, or any other status protected under applicable federal, state or local laws.

Equal access to programs, services and employment is available to all persons. Those applicants requiring reasonable accommodations as part of the application and/or interview process should notify a representative of the Human Resources Department.


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