Sr. Data Scientist

Harnham; United States; Remote; USD 120,000 - 134,000; Full time

Benefits offered by this job

Equity participation

Fully remote working model

Annual bonus up to 20%

Job summary

Harnham is seeking a results-driven ML professional to develop, deploy, and maintain machine learning models in production. You will partner with risk, strategy and analytics stakeholders to solve complex business problems through data science and to translate requirements into deployable solutions.

You will monitor model performance, evaluate new data sources, apply software engineering best practices, and communicate insights to both technical and non-technical audiences.

Qualifications

• Strong commercial experience building and deploying end-to-end ML models.
• Expertise using Python for data science and predictive modelling.
• Experience monitoring, testing, validating, and improving models in production.
• Ability to translate business challenges into analytical solutions.
• Experience working in data-rich, commercially focused environments.
• Background in financial services, fintech, insurance, consulting, risk analytics, fraud analytics, actuarial analytics, customer analytics or related fields is highly beneficial.
• Experience with cloud platforms and modern ML tooling is advantageous.

Responsibilities

• Develop, deploy, and maintain machine learning models in a production environment.
• Partner with risk, strategy, and analytics stakeholders to solve complex business problems through data science.
• Monitor model performance and implement improvements to ensure long-term effectiveness.
• Evaluate new data sources, features, and modelling approaches to improve predictive accuracy.
• Apply software engineering best practices, including testing, version control, and code review.
• Communicate insights and recommendations to both technical and non-technical audiences.
• Contribute to the evolution of machine learning frameworks, tooling, and best practices.

Skills

Machine learning

Python

Production deployment

Model monitoring

Data analytics

Cloud platforms

Communication

Finance domain knowledge

Tools

Git

MLflow

Docker

Job description

| $120,000 - $134,000 Base Salary + 20% Bonus + Equity

The Company

This organization operates at the intersection of technology, data, and financial services. They use advanced analytics and machine learning to support decision-making at scale and are continuing to invest in their data science capabilities as they grow.

Their teams bring together expertise from financial services, fintech, insurance, consulting, and analytics backgrounds, creating a collaborative environment where data-driven thinking is central to the business. They offer the opportunity to work on meaningful modelling challenges with visible business impact.

The Role

• Develop, deploy, and maintain machine learning models in a production environment.
• Partner with risk, strategy, and analytics stakeholders to solve complex business problems through data science.
• Monitor model performance and implement improvements to ensure long-term effectiveness.
• Evaluate new data sources, features, and modelling approaches to improve predictive accuracy.
• Apply software engineering best practices, including testing, version control, and code review.
• Communicate insights and recommendations to both technical and non-technical audiences.
• Contribute to the evolution of machine learning frameworks, tooling, and best practices.

Your Skills & Experience

• Strong commercial experience building and deploying end-to-end machine learning models.
• Expertise using Python for data science and predictive modelling.
• Experience monitoring, testing, validating, and improving models in production.
• Ability to translate business challenges into analytical solutions.
• Experience working within data-rich and commercially focused environments.
• Background in financial services, fintech, insurance, consulting, risk analytics, fraud analytics, actuarial analytics, customer analytics, or related fields is highly beneficial.
• Experience with cloud platforms and modern machine learning tooling is advantageous.

What They Offer

• Base salary of $120,000 - $134,000.
• Annual bonus of up to 20%.
• Equity participation.
• Fully remote working model.
• Exposure to business-critical machine learning initiatives.
• Opportunities for career progression within a growing analytics function.
• Collaborative and supportive working environment focused on continuous learning and development.