Data Scientist II

Early Warning Services; New York (NY); Híbrido; USD 122.000 - 162.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

401(k) Retirement Plan with Safe Harb

Paid Time Off

Holidays & PTO

Descripción de la vacante

Early Warning Services, in a hybrid role in New York, NY, is seeking a data science professional to translate business needs into production-ready models—from data exploration through deployment, validation, and ongoing performance reporting.

Applicants should have a minimum of 4 years in data science or related fields, strong Python/R programming, SQL proficiency, and experience with terabyte-scale datasets. Collaboration with product and engineering teams is expected.

Formación

• Bachelor's degree in Mathematics, Statistics, Computer Science, Operational Research or related field.
• Minimum 4 years of data science, engineering, mathematics, or related work experience.
• Experience developing data science pipelines and workflows in Python, R, or equivalent language.
• Experience writing and tuning SQL.
• Experience handling terabyte-sized datasets.
• Experience applying machine learning techniques with interpretable results.
• Experience with ML libraries such as scikit-learn and mllib.
• Experience using data visualization tools.
• Ability to produce production-level code that is well-written and explainable.

Responsabilidades

• Independently explore and aggregate data to uncover anomalies that can affect algorithm performance.
• Lead end-to-end feature engineering, including brainstorming, creating, validating, and down-selecting features.
• Write production-level code in a dynamic, startup-style environment.
• Solve complex problems using terabyte-scale datasets.
• Apply multiple machine learning techniques to select an optimal approach for business problems.
• Partner with Product and Engineering teams to address problems and identify trends and opportunities.
• Explain and visualize results, as well as algorithm performance, for non-technical audiences.
• Support the company’s commitment to protect the integrity and confidentiality of systems and data.

Conocimientos

Python

SQL

Data Visualization

PySpark

scikit-learn

Educación

Bachelor's degree in Mathematics, Statistics, Computer Science, Operational Research

Herramientas

R

mllib

PySpark

Descripción del empleo

Early Warning Services is building end-to-end machine learning and artificial intelligence solutions with a team that collaborates closely with senior technical and business leaders. In this hybrid role in New York, NY, you will help translate business needs into production-ready models, from data exploration through deployment, validation, and ongoing performance communication.

What you’ll do

• Independently explore and aggregate data to uncover anomalies that can affect algorithm performance
• Lead end-to-end feature engineering, including brainstorming, creating, validating, and down-selecting features
• Write production-level code in a dynamic, startup-style environment
• Solve complex problems using terabyte-scale datasets
• Apply multiple machine learning techniques to select an optimal approach for business problems
• Partner with Product and Engineering teams to address problems and identify trends and opportunities
• Explain and visualize results, as well as algorithm performance, for non-technical audiences
• Support the company’s commitment to protect the integrity and confidentiality of systems and data

Core qualifications

• Bachelor’s degree in Mathematics, Statistics, Computer Science, Operational Research or a related field
• Minimum 4 years of data science, engineering, mathematics, or related work experience
• Experience developing data science pipelines and workflows in Python, R, or an equivalent language
• Experience writing and tuning SQL
• Experience handling terabyte-sized datasets
• Experience applying machine learning techniques, including understanding key parameters that influence performance
• Experience with ML libraries such as scikit-learn and mllib
• Experience using data visualization tools
• Ability to produce production-level code that is well-written and explainable
• Interest in frequent proof of concepts and rapid prototyping
• Ability to communicate findings from complex analyses to non-technical audiences
• Background and drug screen

Preferred qualifications

• Familiarity with model risk management practices, including development documentation, validation review, performance monitoring, and communicating model assumptions and limitations
• Fraud analytics experience, including developing or validating fraud models in a bank or other financial institution
• Banking risk model experience, including models used in CCAR stress testing or CECL estimation
• Experience with transaction or payment data, fraud patterns, and rare event evaluation, including tradeoffs between fraud detection and false positives
• PySpark experience, including scalable feature engineering and reproducible data science pipelines
• Knowledge of advanced machine learning algorithms and selecting methods aligned to business problems and data
• Track record of managing ambiguity, prioritizing work, delivering proofs of concept or model development milestones, and communicating risks and dependencies
• Experience automating data science workflows or adopting shared modeling and feature engineering platforms
• PhD/MSc in Mathematics, Statistics, Computer Science, Operational Research, or a related field

Tools and technologies

Python, R, SQL, scikit-learn, mllib, PySpark, CCAR, CECL

Compensation

New York, NY: USD 122,000 - 162,000 per year.

Additionally, candidates may be eligible for a discretionary incentive plan and the benefits listed below.

Benefits

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

Additional information

• Hybrid work model to support a more collaborative working environment
• Must independently possess eligibility to work in the United States for any employer at the date of hire; no visa sponsorship
• Early Warning Services is an equal opportunity employer
• Pursuant to the San Francisco Fair Chance Ordinance, qualified applicants with arrest and conviction records will be considered