WHAT YOU WILL WORK ON
If this is you, you will be part of an Advanced Analytics squad. We deliver scalable models to power digital demand sensing and enable critical investment decisions. Specifically, you will:
- Develop new sophisticated algorithms and improve existing approaches based on statistical/econometric methods, machine learning techniques and big data solutions to forecast consumer demand and determine optimal level of investment in various stages of the supply chain.
- Assess business requirements and constraints to make trade-off recommendations between speed and accuracy of alternative solution approaches.
- Identify and apply appropriate methods to acquire, explore, cleanse, and fuse data from different sources.
- Be a key contributor to building, scoring, deploying, monitoring, updating and promoting our central forecasting platform.
- Facilitate the planning, scheduling and value measurement of the work to meet timeline targets and success criteria.
- Support the adoption of analytic products through effective storytelling and collaboration with key partners.
WHO YOU WILL WORK WITH
You will work with the Director of Data Science while partner on daily basis with the fellow data scientists, data analysts, engineers and product owner on your squad. You will collaborate across the broader organization with business teams in Demand and Supply Management as well as other data, analytics and technology functions.
WHAT YOU BRING
- Advanced quantitative degree (Statistics, Mathematics, Economics, Computer Science or related field) and at least 5 years of related industry experience or Bachelor’s degree and 7-12 years related industry experience.
- Demonstrated understanding of market demand and supply interactions. Working knowledge of forecasting techniques, such as surveys, trend analysis, econometric models and machine learning algorithms.
- Intermediate to advanced skills in programming languages (particularly Python and SQL) and ability to apply them for data acquisition, preprocessing, modeling and monitoring.
- Familiarity with the wide range of data science/analytics software tools (e.g. Jupyter Notebook, SQL consoles, Hadoop, Spark) and cloud computing platforms (e.g. Amazon Web Services).
- Experience in building, training, scoring, tuning and maintaining predictive models in production at enterprise scale and familiarity with mainstream packages relevant to managing all stages of Data Science/Analytics lifecycle.
- Familiarity with the Agile development process and demonstrable ability to prepare a project plan, communicate the plan to the team and break the work down to trackable tasks.
- Proven track record of working cross functionally and critically evaluate complex business information from multiple perspectives, including questioning assumptions and validity.