Data Scientist - Data Solutions and Initiatives
Location
Cupertino, CA | United States
Job description
The people here at Apple don't just create products - they create the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.
Apple is seeking an experienced, detail-minded data scientist to join our Worldwide Sales Team, Data Solutions & Initiatives (DSI). DSI is a product strategy and engineering team that works closely with business development and sales finance. The ideal candidate will have deep statistics background, can train the model, productize it with proficient programming/platform knowledge, and most importantly, present findings to management/executive groups, effectively summarizing model features, results and predictions.
Key Qualifications
- At least 8 to 12 years of Data science, researching, prototyping, developing, benchmarking, productionalizing, monitoring and overseeing/managing the lifecycle of analytical and AI/ML algorithms to solve complex business problems.
- Applied knowledge of statistical data analysis, predictive modeling classification, Time Series techniques, sampling methods, multivariate analysis, hypothesis testing, and drift analysis.
- Excellent programming skills and working experience in SQL (both relational and cloud databases), Python, Deep Learning architectures, TensorFlow, PyTorch and/or R as well as their standard & commercial analytical packages/tools including pandas, numpy, geopandas, jupyter notebook, etc.
- Proven expertise in data wrangling and developing data visualizations & reporting. Knowledge of tools such as Tableau, Dremio, Dataiku, Snowflake, AWS etc. is desirable.
- Experience with supply and demand forecasting is highly desirable. Sales, finance and operation domain and business process understanding is a plus.
- Excellent written/verbal communication and presentation skills, engagement and interpersonal skills with effective storytelling ability to all levels of an organization.
- Ability to operate comfortably and effectively in a fast-paced, highly cross-functional environment.
- Experience working with Agile methods such as scrum (SDLC) and comfortable with GIT.
Description
We are a rapidly growing team with plenty of interesting technical & business challenges to solve. We seek a self-starter who is willing to learn fast, adapt well to changing requirements, and partner with cross-functional teams to support the organization with analytics for product performance, forecasting and customer insights.
- Design, build, deploy and improve connected data models, algorithms and production-grade scalable machine learning and statistical predictive models and solutions to answer business questions for well-defined data science problems. Focus on speed to value (MVP & iterative approach) and help with ‘productizing’ and improving machine learning models.
- Extract, analyze and visualize medium to large-scale datasets; develop predictive models to infer meaningful insights to create, maintain and troubleshoot supply and demand forecasting models.
- Responsible for building out the suite of Data, AI, and Machine Learning products that deliver measurable business value for Sales and Finance Business community.
- Summarize & communicate complex ideas/assumptions and present findings effectively using data and storytelling to a diverse set of partners.
- Deep analysis of Apple’s data, applying various data discovery and statistical analysis methodologies while partnering internally across AI/ML, IS&T, Sales Finance and Product Marketing.
Education & Experience
BS or MS or PhD in Engineering, Computer Science, Applied Economics/Econometrics, Physics, Statistics, Commerce, Business Predictive Analytics, or Applied Mathematics
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 $170,700.00 and $256,500.00, 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 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.
We are a rapidly growing team with plenty of interesting technical & business challenges to solve. We seek a self-starter who is willing to learn fast, adapt well to changing requirements, and partner with cross-functional teams to support the organization with analytics for product performance, forecasting and customer insights.
- Design, build, deploy and improve connected data models, algorithms and production-grade scalable machine learning and statistical predictive models and solutions to answer business questions for well-defined data science problems. Focus on speed to value (MVP & iterative approach) and help with ‘productizing’ and improving machine learning models.
- Extract, analyze and visualize medium to large-scale datasets; develop predictive models to infer meaningful insights to create, maintain and troubleshoot supply and demand forecasting models.
- Responsible for building out the suite of Data, AI, and Machine Learning products that deliver measurable business value for Sales and Finance Business community.
- Summarize & communicate complex ideas/assumptions and present findings effectively using data and storytelling to a diverse set of partners.
- Deep analysis of Apple’s data, applying various data discovery and statistical analysis methodologies while partnering internally across AI/ML, IS&T, Sales Finance and Product Marketing. BS or MS or PhD in Engineering, Computer Science, Applied Economics/Econometrics, Physics, Statistics, Commerce, Business Predictive Analytics, or Applied Mathematics
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