at GoDaddy.com, LLC in Tempe, Arizona, United States
The Data Scientist at GoDaddy.com, LLC in Tempe, Arizona will extract diagnostic, predictive and prescriptive insights from data to drive business outcomes. Provide statistical and analytical support by 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. Navigate and synthesize complex, multi-source, multi-structure, enterprise-scale datasets to develop end-to-end analytic solutions. Perform hands-on development of descriptive, diagnostic, predictive and prescriptive statistical and analytic models using tools such as Redshift, Hive SQL, Python, Tableau, and R for a variety of business use cases. Operationalize model results and recommendations through interactive reports and dashboards. Perform deep-dives and root-cause analysis of emerging business trends, identifying key drivers and actionable insights on a global scale. Track business improvements using the right critical metrics, conducting pre-post measurements, and demonstrating business value. Lead the end-to-end analytic workflows of business use cases. Build 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). Pull, join, re-shape, and analyze large, disparate and highly complex datasets. Apply experience with data science techniques including linear regression, binary classification, CART, clustering, time series forecasting, and A/B testing. Track projects through the full analytics lifecycle including ideation, data preparation, insights generation and modeling, operationalization, pre-post impact tracking, and quantification of business value.
Minimum Requirements: Requires a Master's degree in Analytics or a related quantitative field plus one year of professional data science experience. The one year of experience must include one year of experience with each of the following: (1) statistical testing framework; (2) building predictive, forecasting, data science, machine learning or analytic models; (3) preparing analytic visualizations; (4) Tableau, R and Python; (5) Hive/SQL; (6) data science techniques including linear regression, binary classification, CART, clustering, time series forecasting, and A/B testing; and (7) full analytics lifecycle.
Interested candidates should submit resume to Nicole Betayeb at: firstname.lastname@example.org. Reference job code 1879 in subject line.To view full details and how to apply, please login or create a Job Seeker account