Mars

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.). Experience with various machine learning methods including classification/tree, SVM and ensemble approaches. Experience developing data science pipelines & workflows in Python, R or equivalent programming languages.. Maven Family Planning – provides support through your Parenting journey including egg freezing, fertility, adoption, surrogacy, pregnancy, postpartum, early pediatrics, and returning to work.

sr data scientist

Come build the next-gen fintech at Early Warning, network operator of Zelle®, where we’re relentlessly focused on empowering prosperity in all its forms. From fast money movement for over 100 million people who can access Zelle® directly through their banking app to new account opening and beyond – we make a difference in the lives of consumers and businesses every day and enable them to live their best financial lives. And we’re only getting started. With new state-of the-art offices in Scottsdale, AZ (Headquarters) and Chicago, IL – plus a growing presence in San Francisco – we’re entering our next big chapter. People matter to us, so we think our best work is done when we’re together, in-person. From informal interactions, to sharing ideas, to mentoring and beyond. We also believe in workplace flexibility and empowering teams to determine the rhythm of work to create an inclusive culture. Through the power of innovative collaboration, we offer hybrid and (when necessary) virtual (“remote”) workplace models. We focus all hiring efforts in a few states and within driving distance of an office location to enable in-person collaboration when and where possible. Priority hiring locations are Scottsdale, AZ, Illinois, NY tri-state metro area (New Jersey, New York and Connecticut) and San Francisco, CA. On exception we will hire in secondary locations such as District of Columbia, Florida, Georgia, Maryland, Nevada, North Carolina, South Carolina, Texas and Virginia. We are not actively recruiting in Colorado, Rhode Island or Washington. Join us and make your mark on what’s next in fintech. Applicants must be authorized to work for any employer in the United States. We are unable to sponsor an employment Visa for this position.
This position will fill a key role on the Data Strategy team, focused on improving our data quality, unifying our data silos, and enriching our data in service of strengthening our ability to reduce fraud and scams. Overall Purpose 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
Data Strategy Focus Brings a formal and rigorous software engineering practice to the efforts of analysts and data scientists, and brings an analytical and business-outcomes mindset to the efforts of data engineering.
Models raw data into clean, tested, and reusable datasets .
Applies various transformations to different data pieces to ensure they correspond to given tasks and to build the foundation layer for dashboards and self-service reporting.
Defines certain metrics to be used and measures to be taken to guarantee data is accurate enough to fit operational and analytics needs.
Works collaboratively with all stakeholders to align business requirements with data assets.
Conducts data mining using state-of-the-art methods.
Must possess good, applied statistics skills, such as distributions, statistical testing, regression, etc.
Experience with data visualization tools, such as tableau, D3.js, GGplot.
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. Early Warning Services is an equal opportunity employer. The pay scale for this position in San Francisco, CA, and New York in USD per year is: a minimum of $125,000 Annually a maximum of $150,000 Annually 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 employee, which is always dependent on legitimate factors considered at the time of job offer. Early Warning Services takes into consideration a variety of legitimate 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. 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.
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