Data Scientist - EMEIA Demand Forecasting & Analytics

do all of this you will be an excellent communicator, collaborator and innovator, with a passion for debate and inclusion.

Description
Our team provides data & automation infrastructure to enable commercial insights for EMEIA Sales Finance and EMEIA Sales. In your role, you will create and maintain data pipelines and machine learning solutions. We help to train and encourage adoption of these technologies with the wider Sales Finance team. You will work in a collaborative environment with minimal formal structure and should be comfortable in a changing environment with competing priorities. You will possess proven business insight, a strong quantitative / technical background, natural curiosity, and the ability to effectively shift between communications styles based on the audience (from a technical peer review through to a leadership update). As this is a role within Finance, you will also be required to have attention to detail as well as strong business and finance acumen.
","responsibilities":"You will manage the end-to-end solution delivery, including:

gathering business requirements
designing and building solutions,
managing testing, training, and rollout

For more complex projects, you may partner with IS&T and Business Process Reengineering teams on delivery. Our team acts as superusers of analytics & BI platforms (e.g. Tableau, SAP BusinessObjects), databases (e.g. Dremio, Snowflake), and data science platforms (e.g. Dataiku).

Preferred Qualifications
Solid understanding of the theory behind statistical analysis and machine learning

Experience in applying data science / machine learning techniques especially times series forecasting to provide solutions to real business problems

Knowledge of machine learning techniques especially for time series forecasting

Experience in developing and maintaining data pipelines

Experience with cloud data science platforms: Dataiku (preferred), DataRobot, Databricks, AWS SageMaker, Google Cloud AI Platform, etc.

Experience in full data science project delivery lifecycle - from identifying the underlying business needs to delivering projects in manner that meets those needs

Curiosity to understand new data science tools and how they can be leveraged to meet business needs

Ability to translate technical content for non-technical audiences and vice-versa

Strong verbal / written communication skills

Creativity to go beyond current tools to deliver the best solution to the problem

Detail oriented and self-motivated individual able to function effectively when working independently or in a team.

Familiarity with MLOps practices is a plus

Experience with Git is a plus

Experience using Tableau is a plus

Experience using Essbase is a plus

Experience using BusinessObjects is a plus

Minimum Qualifications
3-5 yrs experience working as a data scientist, data engineer, data analyst, or related role

2-3 years experience in Python (with emphasis on packages like Pandas, scikit-learn, statsmodels)

Proficiency in query languages such as SQL

Basic knowledge and understanding of software design principles and how to apply them (SOLID, DRY, modularity, abstraction, consistency, etc.)

BS/MS in Data Science/Machine Learning, Mathematics, Statistics, Information Systems, or related field

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. Learn more