We are growing our Data Science team to help Tendam solve challenging problems from the retail fashion industry. We are now seeking a Data Scientist for a unique opportunity of impacting the way the world experiences fashion.

What you will do

1. Decompose complex data problems and conduct rigorous analysis and evaluations
2. Undertake preprocessing of structured and unstructured data
3. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
4. Design, implement and maintain ETL processes to ensure data is available, reliable and ready for analysis and reporting.
5. Develop custom data models and algorithms to apply to data sets
6. Present information using data visualization techniques (Quicksight)

What we are looking for

1. Scientific background with computational and analytical skills
2. Strong problem-solving skills
3. Programming skills with Python and SQL
4. Understanding and experience with big data systems, especially with Spark (PySpark)
5. Knowledge of a variety of machine learning techniques (clustering, regression, decision trees, neural networks, etc.)
6. Experience with data visualization tools and packages
7. A drive to learn and master new technologies and techniques
8. Excellent written and verbal communication skills
9. >2 year of industry experience

Extra qualifications

1. Experience working with huge amounts of data
2. Experience with cloud-based web services (e.g., AWS)
3. Knowledge and experience with a version control system (e.g. Git).

Why Tendam

1. One of the largest customer data repositories in industry: more than 20M Club members
2. Working with multiple different data sources: purchases, marketing campaigns, products, web navigation, apps, etc.
3. Working with cutting edge technologies and building machine learning models to solve real world problems: have a real impact in the business!
4. Ability to immediately test the model results in real pilots: quick time to market!
5. Exposure to agile methodologies
6. Collaborating with a team of Data Scientists in an environment focused on learning, innovation, and professional development.
7. Working in a challenging and dynamic industry