Asks for

The ad says“Strong understanding of core machine learning techniques, including logistic regression, gradient boosting, decision trees, and clustering methods.”
The ad says“Strong understanding of core machine learning techniques, including logistic regression, gradient boosting, decision trees, and clustering methods.”
The ad says“Experienced in designing, executing, analyzing, and reporting on experiments.”
The ad says“Experience in feature engineering, model selection, and performance optimization.”
The ad says“Strong understanding of core machine learning techniques, including logistic regression, gradient boosting, decision trees, and clustering methods.”
The ad says“Strong understanding of core machine learning techniques, including logistic regression, gradient boosting, decision trees, and clustering methods.”
The ad says“Experience in feature engineering, model selection, and performance optimization.”
The ad says“Experience in feature engineering, model selection, and performance optimization.”
The ad says“Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch.”
The ad says“Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch.”
The ad says“Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch.”
The ad says“Expertise in SQL and working with large, complex structured and semi-structured datasets.”
The ad says“Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch.”
The ad says“Proficiency in Python for data analysis and ML, with experience using libraries such as Scikit-Learn, XGBoost, TensorFlow, or PyTorch.”

Senior Data Scientist

About Current

Current is a leading U.S. fintech serving people who have been overlooked by traditional banks. We are one of the fastest-growing companies with nearly 6 million members. Headquartered in NYC, our results-driven environment empowers our team to build better products, grow faster, and have a direct impact on our mission to improve financial outcomes for our members.

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.