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Early Warning

Sr. Data Scientist

Job Posted 14 Days Ago Posted 14 Days Ago
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4 Locations
115K-150K Annually
Senior level
4 Locations
115K-150K Annually
Senior level
The Sr. Data Scientist will develop machine learning techniques to identify at-risk entities in large datasets, document model performance, and mentor junior staff.
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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 senior data science team member in the company developing techniques to identify entities at risk in a moment in time in a multifaceted, high-volume, high-throughput data environment. This position requires extensive background and knowledge in machine learning. Previous experience in analyzing large datasets and developing data-driven statistical models is required.
Essential Functions

  • Identifies, experiments with, and develops appropriate machine learning techniques to extract the value in data from various sources to solve valuable business problems
  • Assists with the development of complex consumer profiles which are used for model training and real-time scoring
  • Take the key role in the development and implementation of product-prototype models
  • Assesses overall performance, stability, and effectiveness of analytically derived models.
  • Documents and presents model process and model performance
  • Collaborates with software engineers to define statistical components for unit testing and acceptance testing
  • Translates high level business objectives into quantifiable analysis tasks.  Identifies and recommends new modeling and analytics opportunities.
  • Remains fluent with emerging technologies and methodologies, shares knowledge, and serves as subject expert and a mentor to junior data scientist
  • Support the company's commitment to protect the integrity and confidentiality of systems and data.

Minimum Qualifications

  • Bachelor’s Degree in Mathematics, Statistics, Machine Learning, Computer Science or related field.
  • A minimum of 6 years working experience in predictive modeling, optimization, and machine learning (or equivalent education and experience).
  • Advanced experience in data mining with a range of advanced technical tools (Python, R, Hadoop, Hive, SQL, Java, Spark, etc.) for timely manipulation of large data sets.
  • Experience with various machine learning methods including classification/tree, SVM and ensemble approaches
  • Experience in utilizing a wide variety of statistical modeling techniques.
  • Experience with understanding business requirement and translating into an analytics design
  • Effective communication skills
  • Proven ability to coordinate or lead data scientists on projects
  • Background and drug screen

Preferred Qualifications

  • PhD/MSc in Mathematics, Statistics, Computer Science, Operational Research or related field; Advanced degree preferred. 
  • Deep knowledge of advanced 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.
  • 2+ years’ experience working with financial data.
  • 4+ 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
     

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 in USD per year is: $115,000 - $135,000.
New York, NY/ San Francisco, CA in USD per year is: $125,000 - $150,000.

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.

 

Additionally, candidates are eligible for a discretionary bonus, and benefits.

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.

 

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. 

Top Skills

Hadoop
Hive
Java
Python
R
Spark
SQL

Early Warning San Francisco, California, USA Office

275 Sacramento St, San Francisco, CA, United States, 94111

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