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!Data ScientistRemotePOSITION SUMMARY:We are seeking an experienced and innovative Data Scientist to join our dynamic team. In this role, you will leverage advanced analytics, machine learning, and statistical modeling to build and support Real Estate forecasting and market optimization. You will partner with the Real Estate team to deliver models and analytics to support the optimal location in the right market to best serve our customers for each of the Signet banners.RESPONSIBILITIES: - Understand and prioritize Real Estate business problems, identify ways to leverage complex data to build and continuously improve forecasting, transfer and optimization models leveraged in re-usable solutions to support Real Estate strategy decisions.
- Visualize complex data sets, draw conclusions and relationships, and develop actionable recommendations
- 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.
- Conduct test-and-learn (A/B, control testing) for measurement of capital projects, competitive locations, store closing/transfer analyses, and trade area/whitespace analytics.
- 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 Real Estate models and analytical techniques including, data blending, statistical modeling, automation of manual processes, and data visualization.
POSITION QUALIFICATIONS: - Bachelor’s degree in data science, Analytics, Statistics, or similar field is required
- Master’s degree in data science, Analytics, Statistics, or similar field is preferred
- 5-7 years of experience in statistical modeling, data science or a related field
Technical/Other Skills Required: - Advanced knowledge of Alteryx, SQL, Python, or R
- Intermediate Knowledge of Tableau (or any other Business Intelligence platform), Microsoft Office Suite, data management concepts
- Intermediate Knowledge of ESRI ArcMap preferred
- 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 spatial data management and spatial analysis
- Experience with AWS tools/environment preferred
- Excellent written and verbal communication skills for preparing reports and presentations
- Strong attention to detail and organizational skills
- Ability to work collaboratively in a team environment and engage with diverse stakeholders
- Self-motivated with a proactive approach to problem-solving
BENEFITS & PERKS: - Competitive healthcare, dental & vision insurance
- 401(k) matching after one year of employment
- Generous time off + company holidays
- Merchandise discount
- Learning & Development programs
- Much more!
The salary range for this opportunity is $113,000 - $133,000. Base pay offered may vary depending on geographic region, internal equity, job related knowledge, skills and experience, among other factors.
