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Job Description:
Role Summary/Purpose: Our Fraud Analytics team integrates data science and engineering to develop intelligent data science solutions, insights and services that improve SYF's fraud risks and customer experience. As a Lead Data Scientist on the Fraud Analytics team, you will be responsible for leading a highly impactful body of work for our partners at Credit, Operation and other teams. You will work with the VP of Fraud Analytics to build a foundation of state-of-the-art capabilities to support a number of ongoing and planned data analytics projects, including descriptive data analytics and predictive modeling, typically involving large scale datasets. In addition, you will be a thought leader and liaison between analytics and the broader business community to help shape and influence the growth of big data analytics within SYF. The goal is to help establish the best practices for data science that modernize the workflow and optimize the collaboration efficiency, to deliver exceptional fraud analytics to our partners for their success. This position is remote, where you have the option to work from home. On occasion we may request for you to commute to our nearest office for in person engagement activities such as team meetings, training and culture events. To ensure the safety of our colleagues and communities, we require employees who come together in-person to be fully vaccinated. We're proud to offer you choice and flexibility. Roles and Responsibilities- Interface with Enterprise Fraud, Fraud Strategy, Fraud Operation, Cyber Security, Technology and other senior leaders to establish productive partnerships in order to democratize data science, deliver innovative solutions and deep insights that directly impact business outcomes i.e. risk, operational, customer experience, regulatory and etc.
- Establish credibility as a trusted advisor to key stakeholders across business units in order to promote and elevate statistical and predictive modeling standards.
- Uncover opportunities to apply data science for business problem solving.
- Communicate findings and recommendations for both executive and technical audiences to influence business decision makings.
- Responsible for the conception, design, prototype, planning, execution and prioritizing of large scale data analytics and predictive modeling projects, as well as experimenting with new models and techniques.
- Collaborate with Technology to create an enterprise level Machine Learning ecosystem which includes the ML platform, tooling, workflow, and governance processes.
- Collaborate with data and software engineers to enable deployment of data products, analytical systems and models that will scale across the company's ecosystem.
- Accountable for code quality and documentation and model documentation per policies and procedures.
- Lead model governance processes with MRM, Legal and Compliance to ensure successful model approvals.
- Perform other duties and/or special projects as assigned
- Bachelor's Degree with preferred concentrations in Mathematics, Statistics, Computer Science, Physical Science, Engineering, or other quantitative discipline. In lieu of degree, a high school diploma and 9+ years of analytics work experience in the financial services, credit card, and/or payment industries.
- 5+ years of progressive work experience including:
- At least 3 years of experience in analytics preferably within Banking Industry.
- At least 3 years of experience in ML model development using large scale data.
- At least 3 years of experience in open source programming languages for large scale data analysis, such as Python, Spark, SQL, Hadoop.
- Advanced degree (PhD, MS) preferred in related field (Data Science, Engineering, Mathematics, Statistics, Computer Science)
- Exceptional communication, partnership, collaboration and influencing skills - ability to translate findings to executive audience to influence decision making.
- Strong ability of managing multiple projects with competing deadlines.
- Fundamental understanding of probability and statistics.
- Ability to employ ingenuity and creative data analysis within a robust statistical framework.
- Strong Machine learning skills e.g., Regression, Classification, Clustering.
- Experience in developing predictive models within an HDFS ecosystem, i.e. Enterprise Data Lake (EDL)
- Experience collaborating with data scientists, data engineers, business analysts, business SMEs
- You must be 18 years or older
- You must have a high school diploma or equivalent
- You must be willing to take a drug test, submit to a background investigation and submit fingerprints as part of the onboarding process
- You must be able to satisfy the requirements of Section 19 of the Federal Deposit Insurance Act.
- New hires (Level 4-7) must have 9 months of continuous service with the company before they are eligible to post on other roles. Once this new hire time in position requirement is met, the associate will have a minimum 6 months' time in position before they can post for future non-exempt roles. Employees, level 8 or greater, must have at least 24 months' time in position before they can post. All internal employees must consistently meet performance expectations and have approval from your manager to post (or the approval of your manager and HR if you don't meet the time in position or performance expectations).
- Federal law requires employers to provide reasonable accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job or to perform your job. Examples of reasonable accommodation include making a change to the application process or work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.
- If you need special accommodations, please call our Career Support Line so that we can discuss your specific situation. We can be reached at Representatives are available from 8am - 5pm Monday to Friday, Central Standard Time.
Vacancy expired!