Manager, Data Science

Denver, CO - Hybrid

Applications have closed

Angi® is transforming the home services industry, creating an environment for homeowners, service professionals and employees to feel right at “home.” For most home maintenance needs, our platform makes it easier than ever to find a qualified service professional for indoor and outdoor jobs, home renovations (or anything in between!). We are on a mission to become the home for everything home by helping small businesses thrive and providing solutions to financing and booking home jobs with just a few clicks.  

Over the last 25 years we have opened our doors to a network of over 200K service professionals and helped over 150 million homeowners love where they live. We believe home is the most important place on earth and are embarking on a journey to redefine how people care for their homes. Angi is an amazing place to build your dream career, join us—we cannot wait to welcome you home!

About the role:

Our Applied Data Science team is tackling challenges such as homeowner-contractor matching, forecasting key business metrics, and using predictive models to optimize consumer experience. This role will give you the opportunity to support a team of dedicated data scientists using state-of-the-art machine learning techniques and big data processing tools to solve some of Angi’s biggest challenges.  This will include driving the strategy and implementation of our data science projects and collaborating with leaders in our Marketing and Product teams.

As a Data Science Manager, you will be responsible for:

  • Leading and developing a best-in-class data science team
  • Creating a strategic vision for the team and develop initiatives aimed to accomplish the vision
  • Building productive and efficient relationships with stakeholders across marketing, data/analytics, product, and finance. Be a champion for your team
  • Learning the complex Angi ecosystem and overall Angi marketing strategy in order to be a subject matter expert on the data, analysis, and modeling
  • Utilizing data to identify opportunities for growth and efficiencies within the marketing program. Communicate and champion these opportunities with stakeholders and constantly push to improve
  • Bringing a deep understanding of marketing and data science strategies with the ability to communicate effectively with stakeholders.

 

Team members in this role are successful when they have a Master’s degree in Statistics, Applied Mathematics or similar quantitative field and/or 7+ years of experience in:

  • Performing quantitative analysis, predictive analytics, mathematical modeling and/or machine learning
  • Proven record of working closely with senior leadership
  • Demonstrating creative problem solving skills to inform decisions, improve outcomes, and deliver transformation through data 
  • Developing predictive models and analysis using R and/or Python
  • Interacting with data using SQL
  • Deep knowledge of machine learning and data mining algorithms
  • Excellent verbal and written communications skills.
  • Ability to manage multiple projects simultaneously.

 

Compensation & Benefits: 

  • The salary band for this position ranges from $150,000-$180,000, commensurate with experience and performance. Compensation may vary based on factors such as cost of living. 
  • This position will be eligible for a competitive year end performance bonus & equity package. 
  • Full medical, dental, vision package to fit your needs 
  • Flexible vacation policy; work hard and take time when you need it 
  • Pet discount plans & retirement plan with company match (401K) 
  • The rare opportunity to work with sharp, motivated teammates solving some of the most unique challenges and changing the world 

#LI-Remote
#BI-Remote

Tags: Big Data Data Mining Finance Machine Learning Mathematics Python R SQL Statistics

Perks/benefits: 401(k) matching Career development Competitive pay Equity Flex hours Flex vacation Health care Salary bonus

Regions: Remote/Anywhere North America
Country: United States
Job stats:  26  6  0
Category: Leadership Jobs

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