Sr. Data Scientist

Merrick Bank

7d•Onsite

About The Position

The Senior Data Scientist is responsible for developing, validating, deploying, and monitoring advanced predictive analytics solutions that drive risk, marketing, and business decision-making across the bank. This role combines deep expertise in traditional statistical modeling and machine learning with the ability to apply emerging AI technologies to solve complex business challenges. The successful candidate will serve as a technical leader within the Data Science & Modeling organization, partnering with business stakeholders, technology teams, and senior leadership to deliver robust analytical solutions. Experience with modern machine learning techniques is required. Exposure to deep learning, large language models (LLMs), and generative AI technologies is highly desirable.

Requirements

Bachelor's or Master’s degree in quantitative fields (e.g. Data Science, Statistics, Applied Mathematics, Computer Science, Machine Learning, Artificial Intelligence, Economics, Engineering, Operations Research, or a related field) is required.
At least one (1) year of hands-on experience building predictive models, machine learning solutions, or advanced analytics applications in financial services or other highly regulated industries.
Experience developing and deploying production-ready analytical solutions.
Strong understanding of statistical modeling methodologies, including logistic regression, linear models, segmentation, forecasting, and model validation techniques.
Strong expertise in machine learning algorithms and model development workflows.
Advanced programming skills in Python, R, and SQL.
Experience working with large and complex data sets.
Strong analytical, problem-solving, and critical-thinking skills.
Ability to communicate complex technical concepts to business stakeholders and executive leadership.
Proven ability to work independently and collaboratively in cross-functional teams.

Nice To Haves

PhD in a quantitative field is preferred.
Exposure to deep learning, large language models (LLMs), and generative AI technologies is highly desirable.

Responsibilities

Develops, validates, and maintains predictive models supporting Credit Risk, Marketing, Balance/Revenue forecasting, Direct Mail Response, and account-level valuation domains.
Provides end-to-end ownership of the model development lifecycle, including problem framing, conceptual design, data analysis, model construction, validation, documentation, deployment, and user enablement.
Applies traditional statistical techniques, including logistic regression, generalized linear models, clustering, and forecasting methods.
Designs and implements machine learning solutions using techniques such as gradient boosting, random forests, ensemble methods, and other advanced analytical approaches.
Develops model monitoring frameworks to ensure ongoing model performance, stability, fairness, and regulatory compliance. Investigate performance issues, identify root causes, and recommend appropriate corrective actions when models do not perform as expected.
Performs complex data analysis and communicate insights, recommendations, and model performance to technical and non-technical audiences.
Supports model governance, validation, compliance reviews, and regulatory examinations through comprehensive documentation and transparent methodologies.
Researches, assesses, and prototypes emerging AI technologies, including large language models, retrieval-augmented generation (RAG), and generative AI applications.
Responsible for complying with all the Bank’s internal control policies and procedures.
Responsible for understanding and complying with all laws and regulations to which the Bank is subject.
Responsible for communicating problems in operations, noncompliance with the code of conduct, noncompliance with laws and regulations, policy violations, or illegal acts.