Data Scientist
3 weeks ago
As the world works and lives faster, FIS is leading the way. Our fintech solutions touch nearly every market, company, and person on the planet. Our teams are inclusive and diverse. Our colleagues work together and celebrate together. If you want to advance the world of fintech, we'd like to ask you: Are you FIS?
About the team
We are the FIS Embedded Finance team, and our mission is to enable developers across all verticals to imagine, create and monetize financial products to profoundly transform the way the entire financial industry consumes services. Today, it's difficult for many businesses to build the financial products they imagine. Whether that's launching a new credit or debit card, a savings account, a lending business, or anything else - there are barriers in the way that require excessive time and effort. We make it trivially easy for businesses to compliantly offer financial products and innovate on their key differentiators rather than spend all their time building and maintaining financial infrastructure. Learn more about us at atelio.com.
About the role
We are looking for a Senior Data Scientist to join our team and play a crucial role in generating insights and supporting data-driven decision making across the organization. You will be responsible for researching, designing, developing, and implementing data science solutions to solve complex business problems.
Note: We have a hybrid work environment in our Seattle/Bellevue, office unless the role or business dictates otherwise.
What you will be doing
- Develop and lead statistical and machine learning efforts in relation to your projects. Our projects leverage machine learning, experimentation, signal processing, time series analysis, geospatial analysis, natural language processing, and more.
- Leverage large scale data processing such as Spark, Hive, and off-the-shelf systems.
- Conduct original analyses to advise and influence product, engineering, and operations efforts. Communicate findings to stakeholders in a clear and concise way.
- Partner with business stakeholders to understand their needs and translate those needs into data-driven solutions.
- Develop and implement machine learning (ML) models to extract insights from data.
- Analyze large datasets to identify trends, anomalies, and opportunities for improvement.
- Participate in the development of data pipelines to ensure the quality and availability of data for analysis.
- Stay up-to-date on the latest data science trends and technologies.
- Identify opportunities to streamline data-related processes, enhance data quality, and improve efficiency in financial operations.
- Propose and implement innovative solutions and best practices.
- Propose and implement innovative solutions and best practices.
- Identify opportunities to streamline data-related processes, enhance data quality, and improve efficiency in financial operations.
- Stay up-to-date on the latest data science trends and technologies.
- Participate in the development of data pipelines to ensure the quality and availability of data for analysis.
- Analyze large datasets to identify trends, anomalies, and opportunities for improvement.
- Develop and implement machine learning (ML) models to extract insights from data.
- Partner with business stakeholders to understand their needs and translate those needs into data-driven solutions.
- Conduct original analyses to advise and influence product, engineering, and operations efforts. Communicate findings to stakeholders in a clear and concise way.
- Leverage large scale data processing such as Spark, Hive, and off-the-shelf systems.
- A master's in Statistics, Computer Science, Math, Physics or a related field.
- 2+ years of relevant professional work experience in a data science or similar role.
- Proven experience applying machine learning and statistical modeling techniques to solve real-world problems.
- Strong programming skills in Python or R.
- Excellent communication and cross-functional collaboration skills to thrive in a fast-paced environment.
- Proven familiarity with code and programming concepts
- Proven familiarity with code and programming concepts
- Excellent communication and cross-functional collaboration skills to thrive in a fast-paced environment.
- Strong programming skills in Python or R.
- Proven experience applying machine learning and statistical modeling techniques to solve real-world problems.
- 2+ years of relevant professional work experience in a data science or similar role.
- Typical qualifications for the role are 5+ years of relevant professional experience or a combination of work experience and advanced education.
- A PhD in Statistics, Computer Science, Math, Physics or a related field.
- Proven ability to self-direct your technical work and scope projects effectively.
- Experience as a data scientist at a company with global operations
- Experience leading and mentoring junior engineers.
- Excellent communication and collaboration skills to influence both technical and non-technical stakeholders.
- Familiarity with statistical analysis, forecasting techniques, and data modeling.
- Familiarity with financial concepts or fintech software.
- Effective communication and collaboration skills, and a history of collaborating effectively with your team and cross-functional stakeholders.
- A strong understanding of security best practices for building enterprise applications.
- A strong understanding of security best practices for building enterprise applications.
- Effective communication and collaboration skills, and a history of collaborating effectively with your team and cross-functional stakeholders.
- Familiarity with financial concepts or fintech software.
- Familiarity with statistical analysis, forecasting techniques, and data modeling.
- Excellent communication and collaboration skills to influence both technical and non-technical stakeholders.
- Experience leading and mentoring junior engineers.
- Experience as a data scientist at a company with global operations
- Proven ability to self-direct your technical work and scope projects effectively.
- A PhD in Statistics, Computer Science, Math, Physics or a related field.
At FIS, we hire the best. In return, you receive exceptional benefits including:
- Opportunities to innovate in fintech.
- Tools for personal and professional growth.
- Inclusive and diverse work environment.
- Resources to invest in your community.
- Competitive salary and benefits.
- Competitive salary and benefits.
- Resources to invest in your community.
- Inclusive and diverse work environment.
- Tools for personal and professional growth.
FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.
EEOC Statement
FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here
For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.
Sourcing Model
Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.
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