Data Scientist I

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 company delivering leading edge machine learning and artificial intelligence concepts from start to finish in collaboration with senior technical and business leaders. This includes understanding the business problem, aggregating, and exploring data, building, and validating algorithms, quantifying the value of the model to Early Warning Customers by performing simulations utilizing real world inputs, understanding, and articulating the model risks, deploying completed models to deliver business results and regularly measuring model accuracy, drift and performance.

Essential Functions

• Produces standard and ad hoc analytic reports.
• Assists with developing, testing, and documenting open-source codes for data analysis and modeling.
• Performs data analysis tasks, which include programming data transformations, interpreting results and investigating root causes.
• Participates in the creation of Internal model validation procedures, supporting external Model Validations, and performing regular model validation as part of the Model Risk Management program.
• 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, fast paced environment
• 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
• Partnering with Sales and Products to perform Customer Value tests to support the company’s business development efforts for current and future Models.
• 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

• Bachelor’s Degree in Engineering, Mathematics, Statistics, Computer Science, Operational Research or related field or equivalent work experience.
• A minimum of 2 years data science, engineering, mathematics, or related work/ intern/ course experience is required with Bachelor's degree or Master's degree without experience (or some internship)
• Able to write Model development technical documents.
• Willingness to troubleshoot system/data issues hindering the analytics environment functionality.
• Experience using data visualization tools.
• Able to write production level code, which is well-written and explainable.
• SAS, Python, SQL or R programming training or experience.
• Experience applying various machine learning techniques and understanding the key parameters that affect their performance.
• Ability to effectively communicate findings from complex analyses to non-technical audiences. Ability to communicate with various levels of employees within the department and proven technical and analytical skills.
• Ability and adaptability to work on multiple projects concurrently, manipulate large data sets and produce business-relevant results.
• Background and drug screen

Preferred Qualifications

• Master’s in Mathematics, Statistics, Computer Science, Engineering, Operational Research, or related field preferred.
• Knowledge of ML algorithms
• Experience using ML-related libraries, such as scikit-learn, pandas, etc.
• Experience in writing and tuning SQL.
• Experience developing data science pipelines & workflows in Python, R or equivalent programming languages.
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
  
  

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.

The base pay scale for this position in:
Phoenix, AZ/ Chicago, IL / Washington, DC in USD per year is: $97,000 - $124,000.
New York, NY/ San Francisco, CA in USD per year is: $116,000 - $149,000.
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.

Early Warning Services is an equal opportunity employer.

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!

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.