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New York, New York, United States
Onsite
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 role applies data science, statistical analysis, experimentation, and machine learning techniques to support consumer product strategy, product performance, customer experience, and growth opportunities. While the role includes model building and advanced quantitative methods, the primary focus is using data science to inform and improve the Paze product experience.
Essential Functions
Explore and aggregate data independently to uncover data anomalies that impact algorithm performance
End to end feature engineering - brainstorm, create, validate, down-select, etc.
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.
Support the company's commitment to protect the integrity and confidentiality of systems and data.
Paze specific:
Apply data science and statistical methods to evaluate Paze product performance, customer behavior, feature adoption, conversion, retention, and product friction.
Partner with Product Management, Engineering, Fraud, Marketing, Design, Operations, and Data Engineering to define success metrics, evaluate hypotheses, and translate insights into product decisions.
Develop analytical frameworks, experimentation approaches, segmentation, forecasting, or predictive models to support Paze product strategy and roadmap priorities.
Translate complex data findings, statistical results, and model outputs into clear, actionable recommendations for product teams, business partners, and senior leadership.
Perform data profiling and validation to ensure analysis is based on accurate, well-understood data; identify data quality issues, risks, and trends and recommend improvements.
Minimum Qualifications
Bachelor’s Degree in Mathematics, Statistics, Computer Science, Operational Research or related field;
Typically a minimum of 4 years data science, engineering, mathematics, or related work experience 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 their 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
Interest to do lots and lots of proof of concepts/rapid prototyping
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.
Knowledge of advanced ML algorithms
2+ years of industry experience in machine learning
Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
Experience exploring data and finding hidden patterns
Prior experience in payments, financial services, fintech, consumer product, marketplace, consulting, or another data-rich product environment.
Experience partnering directly with Product Managers, product leadership, or cross-functional product teams.
Experience with experimentation, A/B testing, causal inference, segmentation, funnel analysis, cohort analysis, forecasting, or predictive modeling.
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:
New York, NY/ San Francisco, CA in USD per year is: $122,000 - $165,000.
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.
#LI-AV
#Dice
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 – Flexible 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.
And SO much more! We continue to enhance our program, so be sure to check our Benefits page here for the latest. Our team can share more during the interview process!
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.
Early Warning Services LLC is a proud participant in E-Verify, a federal program to help ensure a legal and authorized workforce. As part of our hiring process, we electronically verify the employment eligibility of all new hires through E-Verify. For more information on your rights and responsibilities under E-Verify please visit Home | E-Verify.
