We are looking for an Applied Scientist to join the Devices Demand Planning team for the entire device family of products and accessories. We develop sophisticated algorithms that involve learning from large amounts of past data, such as actual sales, prices, merchandising activities, promotions, similar products and product attributes, in order to forecast the demand for our product portfolio. These forecasts are used to determine the level of investment in capital expenditures, ordering material, optimizing inventory allocations and determining financial performance. This role is central to the continued growth of the Device division as we have grown from the first Kindle e-reader to a vast portfolio of Fire tablets, Fire TVs, Echo, and Dash.
You will have an opportunity to work on a mathematical problem, with a large element of unpredictability. You will analyze and process large amounts of data, develop new sophisticated algorithms and improve existing approaches based on statistical models, machine learning algorithms and big data solutions to generate multiple demand plans based on distributions of confidence, so that we can provide the Devices organization with a full assessment of opportunities and risks.
You are an individual with outstanding analytical abilities, excellent communication skills, and are comfortable working with technical teams and systems. You will be responsible for researching, experimenting, and analyzing forecasting strategies and mathematical models. You will also be prototyping the implementations.
- Process and analyze sales data; gather additional data sources that would improve model accuracy
- Analyze price elasticity on promotions and develop algorithms to optimize promotional budgets
- Build mathematical models to represent demand forecasting at various levels.
- Prototype these models by using high-level modeling languages such as R or in software languages such as Python. A software team will be working with you to transform prototypes into production.
- Create, enhance, and maintain technical documentation, and present to other scientists and business leaders.
- PhD in Machine Learning, Statistics, Applied Mathematics or a related quantitative field and 1+ years of industry experience, or a Master’ s degree in the related fields with 2+ years of industry experience
- 3+ years experience building, iterating and validating statistical models
- Strong working knowledge of knowledge management, data cleaning, machine learning, and analytics techniques.
- Fluency in R, Python or a similar modeling language and in SQL
- Proficiency in at least one modern programming language such as Java or C++
- Strong verbal and written communication, influencing and partnership skills
- Ability to convey rigorous mathematical concepts and considerations to non-experts
- Experience with large data sets
- Ability to distill problem definitions, models, and constraints from informal business requirements; and to deal with ambiguity and competing objectives
- Experience designing and supporting large-scale distributed systems in a production environment
- Previous experience in a ML or data scientist role with a large technology company
- Knowledge of scripting for automation (e.g. Python, Perl, Ruby)
- Working knowledge of visualization tools (e.g. Tableau, Shiny, D3)
Catapult provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement promotion, termination, layoff, recall, leaves of absence, compensation and training.