Current

Senior Data Scientist

Current$170K — $220K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of data science experience with machine learning focus
  • Proficiency in Python and libraries like Scikit-Learn and TensorFlow
  • Expert in SQL with large and complex datasets
  • Strong knowledge of machine learning techniques like regression and clustering
  • Experience in feature engineering and model optimization
  • Skilled in designing and analyzing experiments
  • Ability to communicate technical insights to diverse audiences

Responsibilities

  • Design and deploy predictive models and anomaly detection algorithms
  • Conduct extensive data exploration and preprocessing for model quality
  • Evaluate model performance with statistical techniques
  • Execute A/B testing to assess model impact
  • Perform customer segmentation through clustering methods
  • Develop monitoring dashboards and model governance
  • Collaborate with cross-functional teams to integrate models into workflows

Benefits

  • Stock options
  • 401(k) savings plan
  • Discretionary performance bonus program
  • Biannual performance reviews
  • 100% coverage of medical, dental, and vision premiums for you and dependents
  • Unlimited time off and paid holidays
  • Generous parental leave policy
  • Commuter benefits
  • Healthcare and Dependent care FSA
  • Mental health-focused Employee Assistance Programs
  • Healthcare advocacy program
  • Access to mental health apps
  • Team-building activities
  • Modern NYC office with stocked kitchen and catered lunches
Full Job Description
Senior Data Scientist
About the Role

At Current, data is at the core of everything we do. As a Senior Data Scientist on the Data and Growth teams, you will focus on machine learning modeling to build predictive models that help us understand our customers better, improve user experience, and efficiently acquire and retain members. This is a hands-on role focused on solving complex problems, developing and deploying ML models, and driving data-driven decision-making.

Your day-to-day will involve analyzing, preparing, and structuring data; building and optimizing predictive models; leveraging clustering algorithms; and collaborating with cross-functional teams (Product, Engineering, Marketing) to integrate ML solutions into customer-focused strategies and processes.
Responsibilities
  • Design, develop, and deploy predictive classification and regression models, along with anomaly detection models and algorithms.
  • Conduct extensive EDA, feature engineering, and data preprocessing to ensure high-quality input for ML models.
  • Evaluate and optimize model performance using statistical and ML techniques.
  • Design and execute A/B tests to measure and validate model impact.
  • Perform customer segmentation using various clustering techniques.
  • Develop and implement model monitoring dashboards and establish model governance techniques.
  • Collaborate with Analytics, Product, Engineering, and Marketing teams to seamlessly integrate predictive models into workflows.
  • Work with the ML Engineering team to ensure efficient data pipelines and scalable model deployment.
  • Analyze diverse datasets to extract meaningful insights and patterns, identifying actionable opportunities for optimization and innovation.
Qualifications
About You
  • 5+ years of experience in data science with a strong emphasis on machine learning modeling.
  • Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch.
  • Expertise in SQL and working with large, complex structured and semi-structured datasets.
  • Strong understanding of core machine learning techniques, including logistic regression, gradient boosting, decision trees, and clustering methods.
  • Experience in feature engineering, model selection, and performance optimization.
  • Experienced in designing, executing, analyzing, and reporting on experiments.
  • Strong communication skills and ability to present findings to technical and non-technical stakeholders.
  • Master's or higher degree in Data Science, Computer Science, Statistics, or a related field is preferred.
Preferred Skills & Qualifications
  • Experience working in fintech, e-commerce, or other data-rich consumer-facing industries.
  • Familiarity with Google Cloud Platform (GCP) services, particularly Vertex AI and Dataflow, for scalable data processing and model training.
  • Experience with dbt for data modeling.
  • Familiarity with BigQuery or other MPP (Massively Parallel Processing) databases.
  • Experience using the Scala programming language for developing scalable and efficient data pipelines.
Benefits
  • Competitive salary
  • Stock options
  • 401(k) savings plan
  • Discretionary performance bonus program
  • Biannual performance reviews
  • Medical, Dental and Vision premiums covered at 100% for you and your dependents
  • Unlimited time off and paid holidays
  • Generous parental leave policy
  • Commuter benefits
  • Healthcare and Dependent care FSA benefit
  • Employee Assistance Programs focused on mental health
  • Healthcare advocacy program for all employees
  • Access to mental health apps
  • Team building activities
  • Our modern NYC based office with open floor plan, stocked kitchen, and catered lunches

This role has a base salary range of $170,000.00 - $220,000.00. Compensation is determined based on experience, skill level, and qualifications, which are assessed during the interview process. Current offers a competitive total rewards package which includes base salary, equity, and comprehensive benefits.

About Current

Current is a financial technology company that provides mobile banking services. The company's platform offers checking accounts, debit cards, and money management tools, as well as rewards and cashback programs. Current's services are available to individuals and families. The company was founded in 2015 and is headquartered in New York, New York.
Learn more about Current
Size
200 employees
Industry
Net Income
-$10 million
Founded
2015
5 Year Trend
+250%
Revenue
$50 million

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