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Data Scientist, Devices and Services FinTech

DescriptionAre you looking for an opportunity to own a large-scale technology problem? Do you enjoy finding patterns and pushing the boundaries of current possibilities? Are you interested in building reliable and scalable systems that support Amazon's growth? If so, Amazon Devices and Services Finance Technology (FinTech) is the perfect place for you!About The TeamAmazon Devices and Services FinTech is the global team that designs and builds the financial planning and analysis tools for a wide variety of Devices` new and established organizations. From Kindle to Ring and even new and exciting companies like Kuiper (our new interstellar satellite play), this team enjoys a wide variety of complex and interesting problem spaces. They are almost like FinTech consultants embedded in Amazon.About This RoleThe Amazon Devices and Services FinTech team is expanding our data science team that is building a forecasting solution for the Amazon Devices and Services Finance organization, and we are looking for a Data Scientist to join us.As a data scientist, you will dive deep into data from across Amazon's finance organization, extract new insights, drive investigations and algorithm development, and interface with technical and non-technical customers. You will leverage your data science expertise and communication skills to pivot between delivering science solutions, translating knowledge of finance and operational processes into forecasting models, and communicating insights and recommendations to audiences of varying levels of technical sophistication in support of specific business questions, root cause analysis, planning, and innovation for the future.Key job responsibilities• Create various forecasts, including but not limited to Operational Expenses, and drive adoption of these forecasts by various teams within Amazon for financial and operations planning• Continuously innovate through research and the application of the latest machine learning techniques to drive forecasting accuracy improvement• Perform exploratory data analysis to identify business opportunities and develop a plan to address them• Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations• Build customer-facing reporting tools to provide insights and metrics which track forecast performance and explain variance• Utilize code (Python, R, Scala, SQL, etc.) for analyzing data and building statistical and machine/deep learning modelsA day in the lifeIn a typical day as a data scientist at Amazon FinTech, you'll begin by delving into complex datasets, applying your technical expertise in feature engineering and exploratory data analysis to uncover valuable insights. You'll utilize both traditional time series forecasting techniques as well as more advanced machine learning algorithms to build accurate and reliable forecasting models that solve complex business problems like Operational Expense (OpEx) Forecasting. Collaboration with business, engineering, and partner teams is essential, as you'll translate your data-driven forecasts into actionable insights that align with strategic goals. Throughout the day, you'll innovate by adapting new forecasting methods, ensuring your solutions are stable, scalable, and fault-tolerant. Your strong communication skills and attention to detail will help you manage and integrate large datasets, solve unstructured problems, and drive projects to completion in a fast-paced, dynamic environment.Join us and be a part of our dynamic team, driving the future of financial technology at Amazon.Basic Qualifications• Bachelor's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science• 3+ years of data scientist experience• 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience• 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience• Experience applying theoretical models in an applied environmentPreferred Qualifications• Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science• Experience in Python, Perl, or another scripting language• Experience in a ML or data scientist role with a large technology companyAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.Company - Amazon.com Services LLCJob ID: A2853527

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What You Should Know About Data Scientist, Devices and Services FinTech, Amazon

Are you ready to dive into the exciting world of data at Amazon Devices and Services FinTech? We're on the lookout for a passionate Data Scientist in Sunnyvale, CA, who loves unraveling complex data challenges and contributing to innovative forecasting solutions. In this role, you'll get to engage deeply with analytics, transforming raw data into actionable insights that drive the financial planning for our incredible range of devices, from Kindle to future projects like Kuiper. You'll collaborate with cross-functional teams, communicating findings and recommendations effectively, whether you're chatting with fellow data enthusiasts or sharing insights with non-technical team members. Your day-to-day will include utilizing advanced machine learning techniques and statistical models, all while continually improving forecasting accuracy. Imagine the thrill of examining vast data sets to identify trends and forecast operational expenses, contributing directly to our team's success. With your experience in data querying languages and scripting, you'll help build customer-facing reporting tools that empower teams across Amazon. If you're someone who's eager to push the boundaries of what's possible and thrive in a dynamic environment, join us at Amazon Devices and Services FinTech, where your skills can truly shine and make a difference!

Frequently Asked Questions (FAQs) for Data Scientist, Devices and Services FinTech Role at Amazon
What are the key responsibilities of a Data Scientist at Amazon Devices and Services FinTech?

As a Data Scientist at Amazon Devices and Services FinTech, your main responsibilities will include creating innovative forecasts for operational expenses, conducting exploratory data analysis to unearth business opportunities, and collaborating with cross-functional teams to translate complex data into actionable insights. You'll also be advancing forecasting accuracy by applying the latest machine learning techniques and building reporting tools that track forecast performance.

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What qualifications are needed to apply for the Data Scientist position at Amazon Devices and Services FinTech?

To apply for the Data Scientist role at Amazon Devices and Services FinTech, you should hold at least a Bachelor's degree in a quantitative field such as statistics, mathematics, or data science. Additionally, you need 3+ years of experience working with data science, including proficiency in data querying languages like SQL, and programming skills in languages such as Python or R. Familiarity with machine learning tools will also strengthen your application.

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What technologies will I use as a Data Scientist at Amazon Devices and Services FinTech?

In the Data Scientist role at Amazon Devices and Services FinTech, you'll utilize various technologies including Python, SQL, R, and statistical/mathematical software such as SAS or Matlab. You'll be employing machine learning algorithms for data analysis, allowing you to create robust forecasting models essential for the financial planning processes.

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What does a typical day look like for a Data Scientist at Amazon Devices and Services FinTech?

A typical day for a Data Scientist at Amazon Devices and Services FinTech involves delving into complex datasets, applying statistical techniques, and collaborating with various teams to derive actionable insights from your findings. You’ll be busy building predictive models, developing reporting tools, and communicating effectively with both technical and non-technical stakeholders to drive sound business decisions.

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How does collaboration work in the Data Scientist role at Amazon Devices and Services FinTech?

Collaboration is crucial in the Data Scientist role at Amazon Devices and Services FinTech. You’ll be working closely with business stakeholders, fellow data scientists, and engineering teams. This cooperation allows you to translate complex forecasting models into digestible insights for different audiences, ensuring that the solutions developed align with strategic goals and enhance operational efficiency.

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Common Interview Questions for Data Scientist, Devices and Services FinTech
Can you describe your experience with machine learning techniques applicable to financial forecasting?

When answering this question, share specific examples of machine learning algorithms you have implemented for forecasting tasks. Discuss the models you've used and how you've applied them to solve real-world financial problems, emphasizing your understanding of model performance and improvement techniques.

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How do you approach exploratory data analysis in a new project?

To tackle exploratory data analysis, explain that you systematically explore datasets to identify trends, patterns, and anomalies. Discuss the tools and techniques you use, such as visualizations and statistical summaries, and how this initial exploration helps inform your modelling strategy.

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What steps do you take to ensure your forecasts are accurate and reliable?

Detail your methodology for ensuring accuracy in forecasts, which includes selecting appropriate models, validating those models with historical data, and continuously refining based on performance metrics. Mention the use of techniques like cross-validation and performance metrics that you track to evaluate forecasting models.

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How do you handle ambiguous or incomplete data?

Explain that dealing with ambiguous or incomplete data involves a combination of data cleaning, asking targeted questions to stakeholders, and perhaps inferring missing values based on similar data. Discuss the importance of iterative refinement and validation of insights derived from less-than-perfect datasets.

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Give an example of a time you communicated complex data findings to a non-technical audience.

Share a specific instance where you had to present data findings to a non-technical audience. Highlight how you simplified complex concepts, used visuals, and focused on actionable insights to ensure your audience understood and could apply the information effectively.

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What programming languages are you proficient in, and how have you utilized them in your previous roles?

Specify the programming languages you know, such as Python, SQL, and R, and describe projects where you've utilized these languages for data analysis, model development, or reporting. It's important to underline how these skills contributed to the project's success.

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How do you stay updated with the latest trends and advancements in data science?

Discuss your commitment to continuous learning through attending workshops, webinars, reading industry blogs, and participating in online courses. Sharing specific examples of how you've applied new knowledge to your work can also demonstrate your proactive approach.

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What is your experience with building customer-facing reporting tools?

Provide an overview of any reporting tools you've developed, the technologies used, and how these tools have provided actionable insights for clients or internal teams. Emphasize the impact these tools had on decision-making or operational efficiency.

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Describe a challenging data problem you faced and how you solved it.

Share a relevant challenge where you encountered complex data issues. Detail the problem-solving steps you took, including collaboration with teammates, analytical methods applied, and the eventual positive outcome, showcasing your analytical skills and perseverance.

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What role do you think a Data Scientist plays within an organization like Amazon?

Express the critical role a Data Scientist plays at Amazon, emphasizing the contributions to data-driven decision-making, innovation in financial forecasting, and the influence of insights on strategic planning. Discuss how collaboration across departments magnifies the impact of data science on the organization's success.

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Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking.

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CULTURE VALUES
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Transparent & Candid
Growth & Learning
Fast-Paced
Collaboration over Competition
Take Risks
Friends Outside of Work
Passion for Exploration
Customer-Centric
Reward & Recognition
Feedback Forward
Rapid Growth
BENEFITS & PERKS
Medical Insurance
Paid Time-Off
Maternity Leave
Mental Health Resources
Equity
Paternity Leave
Fully Distributed
Flex-Friendly
Some Meals Provided
Snacks
Social Gatherings
Pet Friendly
Company Retreats
Dental Insurance
Life insurance
Health Savings Account (HSA)
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
INDUSTRY
TEAM SIZE
EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
December 15, 2024

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