Data Scientist / Manager - Renewals and Payments Analytics - Mohawk Garnet Inc


: $131,620.00 - $202,650.00 /year *

Employment Type

: Full-Time


: Information Technology

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Job Description

About GoDaddy GoDaddy powers the world's largest cloud platform dedicated to small, independent ventures. With nearly 18 million customers worldwide and over 77 million domain names under management, GoDaddy is the place people come to name their idea, build a professional website, attract customers and manage their work. Our mission is to give our customers the tools, insights and the people to transform their ideas and personal initiative into success. To learn more about the company visit

As a groundbreaking tech company, data drives every aspect of GoDaddy s business. The world-class Business Analytics team at GoDaddy plays a pivotal role in extracting diagnostic, predictive and prescriptive insights from data and driving business outcomes.Renewals and Payments Analytics is a brand new functional area within Business Analytics and is looking to expand further. We are looking for highly motivated and hardworking team members who can unlock the value buried in data and deliver superior outcomes for customers and business partners around the world.This is an exciting role with global scale and scope. Your work will cut across different verticals such as marketing, operations, product, website and pricing, and will have transparency at the topmost levels in the organization. With Renewals and Payments being a greenfield area in the company, you will have high levels of ownership and impact and tremendous opportunities for growth.

  • Working with business partners to understand their goals and objectives, converting business needs into analytic requirements, generating analytic insights, presenting the insights to partners and driving business improvements.
  • Navigating and synthesizing complex, multi-source, multi-structure, enterprise-scale datasets to develop elegant, end-to-end analytic solutions.
  • Hands-on development of descriptive, diagnostic, predictive and prescriptive analytic models using tools such as Redshift, Hive SQL, Python and R for a variety of business use cases.
  • Operationalizing model results and recommendations through interactive reports and dashboards.
  • Carrying out deep-dives and root-cause analysis of emerging business trends, identifying key drivers and actionable insights on a global scale.
  • Tracking business improvements using the right critical metrics, conducting pre-post measurements and demonstrating business value.
  • Leading the end-to-end analytic workflows of business use cases.
  • Building and being responsible for the data and analytic foundation to carry out all of the above activities at scale and at high velocity e.g. production datasets, business logic, data science models, scores and forecasts, measurement frameworks, critical metrics, reports, dashboards and data products.
  • You will have:

  • Minimum 3 years of relevant work experience in an analytics role, preferably in a digital native organization in SaaS/Subscription, e-Commerce or Payments domain.
  • Advanced degree in a quantitative field or a Bachelor s degree with highly relevant experience.
  • Expert proficiency in SQL, ideally in a Big Data ecosystem e.g. Hive or AWS. You are super comfortable with pulling, joining, re-shaping and analyzing large, disparate and highly complex datasets.
  • Command over bread-and-butter data science techniques such as linear regression, binary classification, CART, clustering, time series forecasting, A/B testing.
  • Command over at least one scripting language like Python / R.
  • General programming aptitude and ability to write production-grade code.
  • Expertise with data visualization tools like Tableau. You know how to package and productionize predictive models and diagnostic insights for business users in the form of reports and dashboards.
  • Solid project management skills with the ability to lead multiple priorities and partners.
  • Track record of projects spanning the full analytics lifecycle: ideation, data preparation, insights generation and modeling, operationalization, pre-post impact tracking and quantification of business value.
  • Strong story-telling skills using data.
  • Strong organization and documentation skills.
  • Strong verbal and written communication skills.
  • Strong partnering and teamwork skills.
  • Ability to work independently and make good judgement calls.
  • Ability to work in an agile, fast-paced environment, striking the right balance between short-term, medium-term and long-term objectives.
  • Willingness to take the initiative and keep raising the bar.
  • Can-do attitude and learner mindset, eager and willing to explore new business/technical areas and dive deep.
  • #li-ja1

    GoDaddy is proud to be an equal opportunity employer. We will not discriminate against any applicant or employee on the basis of age, race, color, creed, religion, sex, sexual orientation, gender, gender identity or expression, medical condition, national origin, ancestry, citizenship, marital status or civil partnership/union status, physical or mental disability, pregnancy, childbirth, genetic information, military and veteran status, or any other basis prohibited by applicable federal, state or local law. GoDaddy will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. If you need assistance completing an application for a position with us, please reach out to our Recruiting Team at

    To submit your application to this position, please click Apply . On the next screen, after you click Apply, click Create to establish your candidate account. If you have previously created a candidate account, please slick Sign-In and use that account to complete your application.

    Job ID R005868 Job ID
    Associated topics: chief program officer, cpo, manage, manager, management, monitor, product manager, project manager, relationship manager, task * The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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