Senior Data Scientist

We have many opportunities available on our other career site pages. Click here to link to our careers page!Signet Jewelers is the world's largest retailer of diamond jewelry, operating more than 2,800 stores worldwide under the iconic brands: Kay Jewelers, Zales, Jared, H.Samuel, Ernest Jones, Peoples, Banter by Piercing Pagoda, Rocksbox, JamesAllen.com and Diamonds Direct. We are a people-first company and this core value is at the heart of everything we do, from empowering our valued team members, to collaborating with our customers, to fostering the communities in which we live and serve. People – and the love their actions inspire – are what drive us. We’re not only proud of the love we inspire outside our walls, we’re especially proud of the diversity, inclusion and equity we’re inspiring inside. There are dynamic career paths awaiting you – rewarding opportunities to impact the lives of others and inspire love. Join us!Locations: Dallas, TX or Akron, OHOpen to RemoteRole

This role supports all aspects of Signet North America through use of statistical, predictive, and computer science process, and business knowledge to develop new approaches to discovering insights that lead to business action. Collaborates with multi-disciplinary teams to gather and analyze structured and unstructured data using scientific methods and developing and testing models used to predict business outcomes. Translates statistical results and outcomes into plain-speak so business leaders are fully aware of the implications and can implement changes. Subject matter expert for statistical processes and their implementation (ARIMA, regression, boosted models, decision trees/forest models etc.), and use of tools/languages such as Alteryx, Tableau, R (or R-Studio), Python, SQL, and Business Objects.Responsibilities

Understand and prioritize business problems and identify ways to leverage data to recommend solutions to business problems. Organize and synthesize data into actionable business decisions, focused on insights. Visualize complex data sets, draw conclusions and relationships, and develop actionable recommendations. Provide insight into trends, financial and business operations through data analysis and the development of business intelligence visuals.Work with advanced business intelligence tools to complete complex calculations, table calculations, geographic mapping, data blending, and optimization of data extracts. Properly use linear and non-linear predictive models, and optimization techniques.Develop dashboards and prepare executive level (or targeted audience) presentations to clearly articulate the results of the analysis. Explain, through strong communication skills and analytical analysis, the business value and expected impact of the work. Clearly and fluently translate technical findings to a non-technical team with quantified insights.Capable of executing the full Machine Learning process from collection of data, preparing, cleansing and validating data. Evaluate the advantages of different ML models for a given business problem to develop appropriate features, and create/optimize classification/regression models.Engage and collaborate with analytical team members across the company to increase the organization's analytical capabilities. This includes serving as a subject matter expert on BI tools and analytical techniques including, data blending, statistical modeling, automation of manual processes, and data visualization.Qualifications

Bachelor’s degree in Business, Analytics, Statistics, or similar field is requiredMaster’s degree in Business, Analytics, Statistics, or similar field is preferred7+ years of experience in Data ScienceAdvanced knowledge of various business intelligence tools including - Microsoft Excel, Alteryx, SQL, Tableau, matplotlib, ggplot.Data Wrangling – proficiency in dealing with data imperfections, data gaps, normalization techniques.Experience with statistical data analysis, such as time series, linear models, multivariate analysis, and sampling methods.Experience with SQL, Python, or R is required.Machine Learning – good knowledge to machine learning methods like ARIMA, Naive Bayes, SVM, Decision Forests, Gradient Boosting, Neural Networks.Hands-on experience with data science tools.Experience with git source control system.Experience with AWS tools/environment preferred.Benefits & Perks

Competitive healthcare, dental & vision insurance401(k) matching after one year of employmentGenerous time off + company holidaysMerchandise discountLearning & Development programsMuch more!

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