Data Scientist II

At Early Warning, we've powered and protected the U.S. financial system for over thirty years with cutting-edge solutions like Zelle, Paze, and so much more. As a trusted name in payments, we partner with thousands of institutions to increase access to financial services and protect transactions for hundreds of millions of consumers and small businesses.

Positions located in Scottsdale, San Francisco, Chicago, or New York follow a hybrid work model to allow for a more collaborative working environment.

Candidates responding to this posting must independently possess the eligibility to work in the United States, for any employer, at the date of hire. This position is ineligible for employment Visa sponsorship.

Overall Purpose

This position serves as a data science team member in the Model Validation and Monitoring Team delivering leading edge machine learning models to our clients. This includes providing effective challenges to model development, conduct model monitoring and performance tracking, provide root cause analysis of model performance, exploring, building, validating, and deploying models.

Essential Functions

• Lead model monitoring activities, including tracking performance metrics, detecting model and data drift, identifying data quality issues, providing root cause analysis, and recommending remediation strategies.

• Conduct rigorous model validation by providing effective challenges during model development phases, including performance testing, benchmarking, provide remediation plan, and documentation to ensure models meet business, technical, and regulatory standards.

• Explore and aggregate data independently to uncover data anomalies that impact algorithm performance

  Write production level code in a dynamic, start-up environment

• Solve complex problems using terabyte size data sets

• Apply of a variety of machine learning techniques to a business problem to arrive at optimal approach

• Partner with Product and Engineering teams to solve problems and identify trends and opportunities

• Explain and visualize results and algorithm performance to non-technical audiences

• Support the company's commitment to protect the integrity and confidentiality of systems and data.

Minimum Qualifications

• Educational experience typically includes a Master's degree in Mathematics, Statistics, Computer Science, Operational Research or related field;

• Three or more years of data science, engineering, mathematics, or related work is required

• Experience developing data science pipelines & workflows in Python, R or equivalent programming language. Experience in writing and tuning SQL. Experience handling terabyte size datasets

• Experience applying various machine learning techniques, and understanding the key parameters that affect model performance

• Experience using ML libraries, such as scikit-learn, mllib, etc.

• Experience using data visualization tools

• Able to write production level code, which is well-written and explainable

• Ability to effectively communicate findings from complex analyses to non-technical audiences.

• Background and drug screen

Preferred Qualifications

• PhD/MSc in Mathematics, Statistics, Computer Science, Operational Research or related field; Advanced degree preferred.

• Experience of using advanced ML algorithms building, testing, and deploying fraud models.

• Hands-on experience with PySpark

• 2+ years of industry experience in building or validating machine learning models

• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

• Experience exploring data and finding hidden patterns and data anomalies

Physical Requirements

Working conditions consist of a normal office environment. Work is primarily sedentary and requires extensive use of a computer and involves sitting for periods of approximately four hours. Work may require occasional standing, walking, kneeling, and reaching. Must be able to lift 10 pounds occasionally and/or negligible amount of force frequently. Requires visual acuity and dexterity to view, prepare, and manipulate documents and office equipment including personal computers. Requires the ability to communicate with internal and/or external customers.

Employee must be able to perform essential functions and physical requirements of position with or without reasonable accommodation.

The above job description is not intended to be an all-inclusive list of duties and standards of the position. Incumbents will follow instructions and perform other related duties as assigned by their supervisor.

Early Warning Services is an equal opportunity employer.

The base pay scale for this position in:
Phoenix, AZ/ Chicago, IL in USD per year is: $118,000 - $152,000.
San Francisco, CA in USD per year is: $142,000 - $183,000.
Additionally, candidates are eligible for a discretionary incentive plan and benefits.

This pay scale is subject to change and is not necessarily reflective of actual compensation that may be earned, nor a promise of any specific pay for any specific candidate, which is always dependent on legitimate factors considered at the time of job offer. Early Warning Services takes into consideration a variety of factors when determining a competitive salary offer, including, but not limited to, the job scope, market rates and geographic location of a position, candidate's education, experience, training, and specialized skills or certification(s) in relation to the job requirements and compared with internal equity (peers). The business actively supports and reviews wage equity to ensure that pay decisions are not based on gender, race, national origin, or any other protected classes.

Some of the Ways We Prioritize Your Health and Happiness

• Healthcare Coverage-Competitive medical (PPO/HDHP), dental, and vision plans as well as company contributions to your Health Savings Account (HSA) or pre-tax savings through flexible spending accounts (FSA) for commuting, health & dependent care expenses.
• 401(k) Retirement Plan-Featuring a 100% Company Safe Harbor Match on your first 6% deferral immediately upon eligibility.
• Paid Time Off -Unlimited Time Off for Exempt (salaried) employees, as well as generous PTO for Non-Exempt (hourly) employees, plus 11 paid company holidays and a paid volunteer day.
• 12 weeks of Paid Parental Leave
• Maven Family Planning - provides support through your Parenting journey including egg freezing, fertility, adoption, surrogacy, pregnancy, postpartum, early pediatrics, and returning to work.

AndSOmuch more! We continue to enhance our program, so be sure tocheck our Benefits page here for the latest. Ourteamcan share more during the interview process!

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Early Warning Services, LLC ("Early Warning") considers for employment, hires, retains and promotes qualified candidates on the basis of ability, potential, and valid qualifications without regard to race, religious creed, religion, color, sex, sexual orientation, genetic information, gender, gender identity, gender expression, age, national origin, ancestry, citizenship, protected veteran or disability status or any factor prohibited by law, and as such affirms in policy and practice to support and promote equal employment opportunity and affirmative action, in accordance with all applicable federal, state, and municipal laws. The company also prohibits discrimination on other bases such as medical condition, marital status or any other factor that is irrelevant to the performance of our employees.