Data Scientist

Cupertino,California,United States

Sales and Business Development

Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! Apple’s Sales organization generates the revenue needed to fuel our ongoing development of products and services. This, in turn, enriches the lives of hundreds of millions of people around the world. We are, in many ways, the face of Apple to our largest customers. Apple's US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting, implementing, and operating solutions that have a direct and measurable impact on Apple Sales and its customers. As a US DI Data Scientist, you will employ predictive modeling, data visualization, and statistical analysis techniques to build end-to-end solutions for internal stakeholders, leveraging sales performance data, market data, programs, external data, etc. This role will operate in both capacities, to augment existing data solutions, as well as innovate and trailblazing new data science projects across our RTMs, crafting analytical experiences that transform data into insights and catalyze better decision-making. Analytics is a team sport, and in your role, you will be key in leading and influencing teams on the translation of business problems and questions into data science solutions.

Description

In this role, you will: - Act as a data translator, bridging the gap in expertise between technical teams, made up of data analysts, data scientists, data engineers, software developers, and business stakeholders. - Successfully connecting analytics and business, with the ability to speak the language of both. - Influence upstream data model design, drive KPIs definitions, and develop your e2e data solutions as needed. - Establish a comprehensive roadmap to communicate and manage our commitments and stakeholder expectations while enabling org-wide visibility on progress. - Build and support dashboards and self-service tools (using several platforms) to analyze and present internal and external data. - Leverage available ML/AI models and frameworks across the company.

Minimum Qualifications

• Minimum of a Bachelors's degree in Computer Science, Statistics, Mathematics, Engineering, Economics, Applied Mathematics, Machine Learning, or related field.

• Advanced Degree (MS or Ph.D. preferred) in Electrical Engineering, Physics, Statistics, Mathematics, or similar quantitative field.

• 10+ years of experience in a Data Visualization, Data Science, Data Analysis, or Data Translation role, with a keen eye for design.

• Applied knowledge of statistical data analysis, predictive modeling classification, time series techniques, sampling methods, multivariate analysis, hypothesis testing, and drift analysis.

• Experience with anomaly detection, root cause analysis, and causal inference models.

• Experience articulating and translating business questions into data solutions.

• Proficiency in SQL and experience with at least one major data platform, such as Hadoop, Spark, or Snowflake.

• Expertise with data visualization tools (such as Tableau, D3, Plotly, etc.) for data analysis and presentation. Experience with Tableau Server, TabPy, Extensions, and CSS is a plus.

• Proficiency in programming languages and tools like Python, R, Git, Airflow, and notebooks.

• Ability to develop dynamic presentations that tell a compelling story.

Key Qualifications

Preferred Qualifications

• Strong time management skills with the ability to collaborate across multiple teams.

• Familiarity with cloud and Gen AI paradigms.

• Experience with cross-functional teams on building and deploying semantic layers for LLMs is a plus.

• Able to balance competing priorities, long-term projects, and ad hoc requirements.

• Ability to work in a fast-paced, dynamic, and constantly evolving business environment.

• Strong understanding of data modeling, data warehousing, and ETL concepts. Dataiku experience is a plus.

• Experience with data integration, data management, and data governance tools.

• Great understanding of design processes and design systems.

Education & Experience

Additional Requirements

Pay & Benefits

• At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $195,500 and $293,800, and your base pay will depend on your skills, qualifications, experience, and location.Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.Learn more (https://www.apple.com/careers/us/benefits.html) about Apple Benefits.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

• Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.Learn more about your EEO rights as an applicant. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)

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