EMEIA Sales Finance - Data Scientist at Apple

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

12 Jan, 26

Salary

0.0

Posted On

14 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, SQL, Data Pipelines, MLOps, Statistical Analysis, Time Series Forecasting, Data Science, Dataiku, AWS, GCP, Communication, Creativity, Detail Oriented, Self-Motivated, Collaboration

Industry

Computers and Electronics Manufacturing

Description

Apple is a place where extraordinary people gather to do their best work. Together we create products and experiences people once couldn’t have imagined - and now can’t imagine living without. If you’re motivated by the idea of making a real impact, and joining a team where we pride ourselves in being one of the most diverse and inclusive companies in the world, a career with Apple might be your dream job! You will become a member of the Sales Finance team at Apple. With approximately 150 employees based across 4 regional hubs within EMEIA (Europe, Middle East, India and Africa), we create value, collaborating with many teams to provide outstanding commercial and financial support. We set the bar high; go out of our way to help others; share knowledge; filter out noise to focus on the essential; encourage the very best from ourselves and the team; and drive the right course of action. To 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. We superusers of analytics & BI platforms (e.g. Tableau, SAP BusinessObjects, and various internal tools), databases (e.g. Dremio, Snowflake), and data science platforms (e.g. Dataiku). We help to train others and encourage adoption of these technologies in the wider EMEIA Sales Finance team. As a Data Scientist, you will be a key driver of our machine learning forecast initiative, supporting the demand forecasting function in Sales Finance. You will be responsible for the end-to-end lifecycle of machine learning models - from ideation and data exploration to deployment and monitoring in a production environment. You will collaborate with cross-functional teams of finance analysts, project managers, and other data scientists to solve some of our most challenging problems and drive AIML adoption across Sales Finance. MINIMUM QUALIFICATIONS 5 years of hands-on experience building and deploying machine learning models in a production environment. Strong proficiency in Python and its core data science libraries (e.g. pandas, scikit-learn, statsmodels, NumPy, PyTorch, TensorFlow, LightGBM) Strong proficiency in SQL with hands-on experience querying and manipulating data in modern data platforms like Snowflake or Dremio Experience in developing and maintaining data pipelines Demonstrable experience with MLOps principles and tools, including workflow orchestration frameworks (e.g. Metaflow). Experience in applying machine learning techniques to provide solutions to real business problems, including for time series forecasting Solid understanding of the theory behind statistical analysis and machine learning Experience with cloud data science platforms: Dataiku (preferred), DataRobot, Databricks, AWS SageMaker, Google Cloud AI Platform, etc. Basic experience with deploying infrastructure on cloud platforms like AWS or GCP Basic knowledge and understanding of software design principles and how to apply them (SOLID, DRY, modularity, abstraction, consistency, etc.) Experience in full data science project delivery lifecycle - from identifying the underlying business needs to delivering projects in a 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. BS/MS in Data Science/Machine Learning, Mathematics, Statistics, Information Systems, or related field PREFERRED QUALIFICATIONS Familiarity with MLOps practices is a plus Experience with Git is a plus Experience using Tableau is a plus Experience using BusinessObjects is a plus

Responsibilities

As a Data Scientist, you will drive the machine learning forecast initiative and support the demand forecasting function in Sales Finance. You will manage the end-to-end lifecycle of machine learning models and collaborate with cross-functional teams to solve complex problems.