Staff Data Scientist
US WA BEL 500 STE 300
Applications have closed
FIS
FIS is fintech for bold ideas. FIS is behind the financial technology that transforms how we live, work and play.Job Description
Responsibilities
Demonstrate ownership across all data science aspects of products, ranging from data streams to machine learning, from observability to product strategy
Architect and help build state-of-the-art, robust, efficient, and observable statistical and machine learning models
Develop large-scale data pipelines using off-the-shelf data tools to optimize quality and performance
Create frameworks to identify trends, anomalies, and opportunities, providing actionable insights for product, engineering, and operations teams
Collaborate with business stakeholders to understand their needs and translate them into data-driven solutions
Clearly communicate findings and insights to cross-functional stakeholders, and drive roadmap
Stay current with the latest trends and technologies in data science, machine learning and artificial intelligence, and communicate internally
Help junior scientists grow via technical leadership and mentorship
Requirements
PhD in Statistics, Computer Science, Math, Physics, Economics, Data Science, Engineering, or a similar quantitative field
8+ years of experience in a data science role or similar
Proven experience applying machine learning and statistical modeling techniques to a range of real-world problems
Strong programming skills in Python, SQL, with familiarity in coding concepts and version control via git
Expertise in traditional machine learning and neural network (Keras, TensorFlow, PyTorch) frameworks
Proven experience leading and mentoring junior data scientists, and establishing a high bar for technical excellence
Excellent communication and cross-functional collaboration skills, thriving in fast-paced environments
Proficiency with feature stores, machine learning model governance, model monitoring, A/B testing, and champion/challenger setups
Experience with real-time data processing (Kafka, Flink, Azure Stream, Spark), and cloud-based technologies (AWS, Azure, GCP)
Preferred Qualifications
Published state-of-the-art research in recognized journals and conference talks
Familiarity with payment networks, banking systems, and fintech software
What We Offer
At FIS, we hire the best. In return, you’ll receive:
Opportunities to innovate in fintech
Tools for personal and professional growth
An inclusive and diverse work environment
Resources to invest in your community
Competitive salary and benefits
Privacy Statement
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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Tags: A/B testing AWS Azure Banking Computer Science Data pipelines Economics Engineering FinTech Flink GCP Git Kafka Keras Machine Learning Mathematics ML models PhD Physics Pipelines Privacy Python PyTorch Research Security Spark SQL Statistical modeling Statistics TensorFlow Testing
Perks/benefits: Career development Competitive pay Startup environment
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