Location: Dusseldorf, Germany
Languages: Fluent English, German is desirable
Start Date: postponed, without any expectation of starting date
Duration: 3 months initially, likely to extend
Workload: up to 4 days a week: 3 days on-site, 1 day remote
Apply to: firstname.lastname@example.org
Our client is a market leader industry in the field of home appliances.
As a Data Scientist working within a product team you’ll make significant impact on the direction of identifying product failures before the end customer is affected by an actual failure, delivering maximum satisfaction and maximum comfort to end customers.
You will be working in the field of Data Science, in an assignment of 3 (three) months for the initial deliverables, with strong possibilities of extension as the project matures and is rolled out to production.
Being an experienced contractor in the field of Data Science, you’ll apply your expertise in quantitative analysis, data mining, statistics modelling and forecasting. The aim is seeing beyond the numbers and forecasting when and how devices fail.
- Deriving insights from smart meter, customer and product usage data;
- Building models of user behaviour for statistical analysis;
- Identifying data sources and research approaches which would improve our capabilities;
- Understanding device lifetime, behaviour and and trends;
- Evaluating and defining metrics and identifying levers which move them;
- Designing and evaluating key product metrics, understanding root causes of failures;
- Build a forecasting model;
- Building and analyzing dashboards and reports;
- Managing data or contribute for such aim;
- Working in Python / Databricks platform / MS-SQL / Azure Data Factory;
- Building key data sets to drive your operational and exploratory analysis;
- Working with developers to automate analysis;
- 1+ years of product analytics/data science experience, ideally in related industries, otherwise on a range of problems including time series modelling, and always translated to true commercial impact;
- Working knowledge of analytics and data science domains, including statistics, machine learning and predictive modeling, experimental design, and optimisation;
- Proven ability to initiate and drive commercial projects to completion with minimal guidance;
- Degree or equivalent experience in Computer Science, Mathematics, Physics, Statistics, or other technical fields;
- Experience in cloud data services, AWS, Azure, GCP, etc
- Experience with time series data modelling.
- Fluency in SQL and Python;
- Able to adequately document your work so others can pick it up and evolve it to their needs;
- Ability to present and communicate data driven results clearly, concisely and effectively;