What you'll doThe Senior Data Scientist, Predictive Modelling develops predictive and prescriptive solutions that can be integrated into key enterprise decisions (product forecasting and replenishment, pricing strategy, and promotion optimization). You will conduct traditional and machine learning analytics to identify and quantify cause-and-effect relationships. You will play a key role in the delivery of our advanced analytics roadmap and the development of predictive modelling/machine learning capabilities, while continuing to support the business with traditional analysis and established processes.
The primary responsibilities of this role include:
- Use predictive/statistical modelling techniques and traditional analytics to identify and quantify sales drivers, conduct what-if scenario analysis and measure the causal impacts
- Work with cross functional teams to ensure model predictions and recommendations are consistent with business expertise, explainable, and efficiently integrated into processes
- Plan, track, and manage multiple projects and requests - these initiatives can range from formal long-term project implementations, medium-scale process improvement initiatives, urgent system/tool support issues, or quick ad-hoc analysis requests
- Proactively identify opportunities and deliver data-supported insights to help improve the accuracy of forecasts and key business decisions
- Provide leadership and direction to the team, including training and coaching in advanced analytics
- Act as a subject matter expert for established model implementations and methodologies
Who you areWe are looking for individuals who are:
- Action oriented, and comfortable taking calculated risks to better serve our customers and business
- Outcome focused, critical thinkers with the ability to analyze and visualize, to ensure continuous improvement across our entire business
- Collaborative team players with superior influencing skills, who build relationships easily across various stakeholder groups to move initiatives forward
If you're curious, ready to take on new challenges and open to doing things differently to help us evolve rapidly, then this is definitely the place to be.
What you bringThe dynamic environment requires individuals with a cross functional background, excellent organizational skills, experience working in a project environment, advanced analytical ability, strong communication skills and the ability to work effectively in a team as well as independently.
- 4+ years work experience in data science, modelling, and analytics (merchandising or supply chain preferred).
- University degree (graduate preferred) in engineering, math, computer science, statistics, business or related field
- Proficiency with programming in Python, PySpark, SQL.
- Experience with data science disciplines, including machine learning, data transformation/engineering, data validation, visualization, and successfully implementing and productionizing of projects.
- Strong analytical, problem solving, and data mining skills with the ability to summarize and deliver actionable insights and recommendations.
- Experience with Cloud computing environments for data science. Knowledge of Azure and Databricks would be an asset.
- Results-oriented, with proven project and time management skills (planning, prioritizing, executing, delegating, and tracking).
- Business mindset with an understanding of the retail industry.
- Demonstrated ability to lead, influence, and motivate peers as well as others without direct authority.
- Effective written and verbal communication skills, including presentation abilities.
Broadband Salary Range: $64,000 - 106,000
Salary decisions are also dependent on other factors such as your experience, industry benchmarks, internal equity and other role-specific requirements. For critical roles, the compensation offering will be reviewed to ensure alignment with market rate and conditions and the unique value you bring to the role. #LI-NZ2
This posting represents an existing vacancy within our organization.
We may use artificial intelligence tools as part of our recruitment process to assist in the initial screening of resumes. All hiring decisions, including candidate evaluation, selection, and disposition, are made by human recruiters.
