Data Scientist

16 hours ago


Hyderabad, Telangana, India Apple Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Apple is a place where extraordinary people assemble to do their best work. Together we craft products and experiences people once couldn't have invented - and now can't imagine living without. If you're looking forward to a real impact and joining a team where we pride ourselves in being one of the most diverse and expansive companies in the world, a career with Apple might be your next job.

The Wallets, Payments, and Commerce (WPC) team at Apple is looking for a full-stack Data Scientist who is passionate about crafting and implementing data solutions that have a direct and measurable impact on Apple customers. You will employ predictive modeling and statistical analysis to build end-to-end solutions for improving the adoption of Apple wallet, alternative payment methods, and core commerce platform. You will be a thought partner to the business, understand strategic goals, and then use your skills and domain expertise to surface actionable insights that drive business decisions and customer benefits. You will collaborate with partners across product, design, engineering, and business teams to drive your recommendations into action. We believe on getting things done iteratively and rapidly, with open feedback and debate along the way. We believe Data Science is a team sport, but we strive for independent decision-making and taking smart risks.

Description

As a data scientist at Apple, you'll be instrumental in measuring launch initiatives and unlocking optimization ideas. You will be collaborating with a team of data engineers, visualization specialists, instrumentation engineers and play a significant role in building data sets and data products that empower you to deliver relevant recommendations. Your primary responsibility will be to drive innovation, embrace new technologies, and ensure that data science aligns with Apple's evolving business needs. You'll present your analysis in multiple forums and also to leadership to optimally communicate your powerful insights and make data-driven recommendations.","responsibilities":"Conduct ad-hoc analyses to support major initiatives, measure impact, and generate insights.

Communicate insights and strategic recommendations to Product, Business, Engineering, and Executive collaborators.

Develop data requirements, establish product critical metrics, and evangelize data products

Design, deploy, and evaluate experiments for improved business performance, and better customer experience

Conduct exploratory analyses, and deliver impactful data solutions with appropriate ML optimization

Explore how new technologies, such as generative AI, can be applied to develop business value.

Partner with teams across Apple to support responsible data collection, governance, and access.

Preferred Qualifications

Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Economics, Engineering) or related quantitative field or relevant professional experience

Experience in a large-scale e-commerce business.

Advanced degree or equivalent experience in Applied Econometrics, Statistics, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field.

Deep understanding of ML algorithm and prior AI development experience.

Minimum Qualifications

Minimum of 3+ years of experience as a Data Scientist or Analyst in commerce, payments, product, or tech environments, with a proven track record of optimization

Understanding of relational databases, including SQL, and large-scale distributed systems such as Hadoop

Ability to implement data science pipelines and applications in a programming language such as Python, or Scala

Prior experience in machine learning algorithms such as classification, regression, clustering, and anomaly detection.

Ability to extract significant business insights from data and identify relevant patterns

Ability to break down complex data for the senior business executives","internalDetails":null,"eeoContent":null


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