Data Scientist, Devices and Services FinTech
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Business Data Scientist Job Listings
The Business Data Scientist role is responsible for analyzing data and contributing to the development of business strategies. Job postings typically look for strong analytical skills, advanced data analysis abilities, and solid business knowledge. Candidates are expected to have experience in areas such as data mining, statistical modeling, and machine learning.
What Does a Business Data Scientist Do?
A Business Data Scientist analyzes datasets and provides strategic recommendations to guide business decisions. The main duties of this role include analyzing large datasets, generating insights to improve business processes, and presenting findings using data visualization techniques. They also support the development of decision support systems, prepare reports, and produce data-driven solutions that guide the company.
What Should Be Considered When Reviewing Business Data Scientist Job Listings?
When applying for Business Data Scientist roles, applicants should pay close attention to the technical skills and qualifications listed in the job description. Proficiency in data analysis, machine learning, and programming languages such as Python or R is essential. Additionally, sector-specific knowledge and experience mentioned by the employer can increase a candidate’s suitability for the position. Job listings usually include details about the scope of the role, expected outcomes, and ongoing projects, all of which should be reviewed carefully.
What Education and Certifications Are Required for Business Data Scientist Positions?
To work as a Business Data Scientist, a bachelor's or master’s degree in fields such as computer engineering, statistics, mathematics, or data science is typically required. Certifications and training in data analysis and machine learning can strengthen a candidate’s resume. Job listings often require proficiency in specific programming languages and tools (such as SQL, Python, Tableau).
What Qualities Are Employers Looking for in Business Data Scientists?
Employers usually seek professionals with strong analytical thinking, excellent problem-solving skills, and the ability to make data-driven decisions. Good communication skills are crucial for clearly reporting and presenting data-based insights. Teamwork skills and the ability to lead projects are also commonly desired.
What Career Opportunities Are Available for Business Data Scientists?
The Business Data Scientist role is highly common across many sectors, especially in data-heavy industries such as finance, technology, healthcare, and retail. Companies offering big data analytics, machine learning, and AI solutions frequently require this position. Consulting firms and data analytics-focused startups are also among the organizations seeking Business Data Scientists. Career opportunities in this field continue to grow rapidly.
How Can I Apply for Business Data Scientist Job Listings?
When applying for Business Data Scientist positions, highlight your data analysis projects and relevant experience in your resume. The application process often includes technical interviews, data analysis exercises, and problem-solving tests. For this reason, building a portfolio that matches the role’s requirements is beneficial. It is also important to include details about your proficiency in programming languages, statistical modeling knowledge, and experience with relevant tools.
In Which Areas Can a Business Data Scientist Work?
A Business Data Scientist can work in various fields such as software development, data analytics, financial analysis, marketing analytics, and operational efficiency. They also play a key role in projects involving artificial intelligence and machine learning. As the need for collecting, processing, analyzing, and interpreting data increases across all industries, the importance of this role continues to grow.
Which Programming Languages Are Required in Business Data Scientist Job Listings?
For Business Data Scientist positions, candidates are typically expected to be proficient in programming languages such as Python, R, and SQL. These languages are widely used for data analysis, modeling, and visualization. Additionally, familiarity with data processing and visualization tools (such as Tableau or Power BI) is an advantage for applicants. Mastery of the programming languages and tools listed in job postings can significantly increase the chances of a successful application.
Data Scientist, Devices and Services FinTech
26.11.2025
ABD
Deneyim: 2-4 Yıl
Type of Work: Tam Zamanlı
Work Location: Uzaktan
Department Level: Uzman
Job Description
Description
Are 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 THIS ROLE
The Amazon Devices and Services FinTech team is expanding our data science team that is building forecasting solutions and advanced analytics platforms 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, building product analytics for our AI systems, 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
- Build product metrics, monitoring pipelines, and analytics tools for our AI assistant to track performance, user engagement, and system reliability
- Continuously innovate through research and the application of the latest machine learning techniques to drive forecasting accuracy improvement and AI system optimization
- Perform exploratory data analysis to identify business opportunities and develop plans to address them across both financial forecasting and AI product development
- 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 and dashboards to provide insights and metrics which track forecast performance, AI assistant effectiveness, and explain variance
- Utilize code (Python, R, Scala, SQL, etc.) for analyzing data and building statistical and machine/deep learning models for both financial forecasting and AI product analytics
A day in the life
As a data scientist at Amazon Devices and Services FinTech, you'll dive into complex datasets using advanced analytics and machine learning to build accurate forecasting models for problems like Operational Expense forecasting. You'll also develop product metrics and monitoring pipelines for our AI assistant, analyzing user engagement and system performance. Collaboration with business and engineering teams is essential as you translate insights into actionable recommendations. Throughout the day, you'll innovate by adapting new forecasting methods and AI analytics approaches, ensuring solutions are scalable and reliable. Your communication skills help you solve unstructured problems in our fast-paced, dynamic environment.
About the team
Amazon 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. We also own and operate the organization's AI assistant, making us true FinTech innovators embedded within 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 environment
Preferred 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 company
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Candidate Criteria
Education Level: Lisans
Language: İngilizce
Military Service Status: Farketmez
University Department: All departments
Skills
About Company
About Amazon
Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are not afraid to fail. We have the scope and capabilities of a large company, and the spirit and heart of a small one. Together, Amazonians research and develop new technologies from Amazon Web Services to Alexa on behalf of our customers: shoppers, sellers, content creators, and developers around the world. Our mission is to be Earth's most customer-centric company. Our actions, goals, projects, programs, and inventions begin and end with the customer top of mind. You'll also hear us say that at Amazon, it's always "Day 1." What do we mean? That our approach remains the same as it was on Amazon's very first day - to make smart, fast decisions, stay nimble, invent, and focus on delighting our customers.
