Data Scientist

Purpose & Overall Relevance for the Organization:

A Data Scientist is a specialist who applies their expertise in statistics and building machine learning models to make predictions and answer key business questions. They focus on understanding, cleaning and analyzing data from the past and present perspectives and producing reliable predictions for the future.

Key Responsibilities:

Analytics:

• Applies a range of mathematical, statistical, predictive modelling or machine-learning techniques in consultation with experts if appropriate, and with sensitivity to the limitations of the techniques.
• Selects, acquires and integrates data for analysis.
• Develops data hypotheses and methods, trains and evaluates analytics models, shares insights and findings and continues to iterate with additional data.

Business Analysis:

• Investigates operational needs and problems, and opportunities, contributing to the recommendation of improvements in automated and non-automated components of new or changed processes and organization.
• Assists in defining acceptance tests for these recommendations.

Data Modelling and Design:

• Applies data analysis, design, and modelling techniques to establish, modify or maintain a data structure and its associated components (entity descriptions, relationship descriptions, attribute definitions).

Programming/Software Development:

• Designs, codes, verifies, tests, documents, amends and refactors moderately complex programs/scripts.
• Applies agreed standards and tools, to achieve a well-engineered result.
• Collaborates in reviews of work with others as appropriate.

Data Visualization:

• Applies a of variety visualization techniques and designs the content and appearance of data visuals.
• Operationalizes and automates activities for efficient and timely production of data visuals.
• Selects appropriate visualization approach from a range of applicable options.
• Contributes to exploration and experimentation in data visualization.

Requirements Definition and Management:

• Assists in the definition and management of requirements.
• Uses standard techniques to elicit, specify, and document requirements for simple subject areas with clearly-defined boundaries.
• Assists in the creation of a requirements baseline and in investigating and applying authorized requests for changes to base-lined requirements, in line with change management policy.

If required: People Management / Resource Management:

• May be involved and gives some input on hiring Transition decisions
• Ensures appropriate leadership skills are present at every level through creating a motivational and supportive work environment in which employees are coached, trained and provided with career opportunities through development
• Allocates the different work to the respective employees considering experience, complexity, workload and organizational efficiency
• Continuously monitors and evaluates team workload and organizational efficiency with the support of IT systems, data and analysis and team feedback and makes appropriate changes to meet business needs.
• Provides team members/direct reports with clear direction and targets that are aligned with business needs and GIT objectives

Key Relationships:

• Global IT
• Respective business function (GOPS, Finance, HR, Brand Marketing, Wholesale/Retail)
• Digital
• Controlling

Requisite Education and Experience / Minimum Qualifications:

• You have solid skills in Machine Learning (in particular tree-based models, NLP, image processing), exploratory data analysis and feature engineering. 
• Understanding of statistics/ statistical inference. Knowledge of linear algebra, optimization and time-series modeling would be a plus. 
• You have a good command of Python and its state-of-the-art analytical libraries (e.g., pandas, scikit-learn, PySpark, plotly). You know the basics of Deep Learning architectures (e.g., CNNs or RNNs) and you are happy to experiment with tools like TensorFlow or PyTorch. Basic knowledge of R (including tidyverse) is an advantage. 
• You are set up for success if you effortlessly work in a Jupyterlab/ Notebook environment and with IDEs like PyCharm or Visual Studio Code. In addition, you know how to use Bitbucket/ GIT for version control and collaborative coding. Familiarity with Databricks/ Sagemaker would be a plus. 

• Solid understanding of relational databases and the ability to efficiently query large databases (e.g., via Spark, SQL, Hue). 
• Familiar with basic software engineering principles (e.g., integration/ unit testing) and the concept of continuous integration. Experience in the use of Jenkins would be a plus. 
• Ideally, you have already experience in one of our focus areas (i.e., recommender and ranking systems, website personalization, search engine optimization, product ranging, sizing, tactical pricing, demand forecasting, image processing, social media listening, customer lifetime value). 
• Experience as a member of an agile development team. 
• 4 years professional experience (inside or outside academia), ideally with a focus on online retailing or sporting goods industry. 
• Excellent communication skills (English, written and oral).
• You interact confidently with developers and stakeholders alike and can present your work to technical and non-technical audiences.