Senior Data Scientist (Credit)

Harnham; United States; Remoto; USD 120.000 - 134.000; Tempo pieno

Vantaggi offerti da questo lavoro

20% annual bonus

Equity participation

Fully remote working

Descrizione del lavoro

Harnham is hiring a Senior Data Scientist to own end-to-end ML lifecycles, from feature engineering to production deployment. You will build models for credit risk, forecast outcomes, and help steer business decisions with measurable results.

You will collaborate with business stakeholders, monitor performance, and explore new data sources to improve accuracy and value. This is a fully remote role with equity potential.

Competenze

• Strong commercial experience building predictive machine learning models.
• Experience deploying models into production environments.
• Strong Python skills with scikit-learn.
• Experience solving business problems through statistical modeling and ML.
• Ability to communicate technical findings to non-technical stakeholders.
• Practical, delivery-focused approach to data science.

Mansioni

• Develop, deploy, and improve ML models that support critical business decisions.
• Build supervised ML models from development through production.
• Design predictive models for risk and decisioning strategies.
• Translate real-world challenges into scalable data science solutions with stakeholders.
• Monitor model performance and identify optimization opportunities.
• Investigate model drift and implement enhancements.
• Test and validate models for reliability and business value.
• Evaluate new data sources, features, and modeling approaches.

Conoscenze

Predictive modeling

Production deployment

Python (scikit-learn)

Statistical modeling

Stakeholder communication

Delivery-focused

Strumenti

scikit-learn

Descrizione del lavoro

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

This is an excellent opportunity for a Senior Data Scientist to join a growing data science team where machine learning models directly influence business decisions. The role is focused on predictive modeling, credit risk, and model performance in production, making it well suited to candidates who enjoy owning the full lifecycle of a model and driving measurable impact through data science.

The Company

They are a technology-driven financial services business using advanced analytics and machine learning to improve decision-making and customer outcomes. Data science plays a central role in the organization, with close collaboration between technical and business teams. The environment is highly collaborative, commercially focused, and suited to individuals who enjoy solving complex problems in a practical way.

The Role

You will develop, deploy, and improve machine learning models that support critical business decisions.

Responsibilities include:

• Building supervised machine learning models from development through to production
• Designing predictive models that support risk and decisioning strategies
• Partnering with business stakeholders to translate real-world challenges into scalable data science solutions
• Monitoring model performance and identifying opportunities for optimization
• Investigating model drift and implementing model enhancements
• Testing and validating models to ensure reliability and business value
• Evaluating new data sources, features, and modeling approaches
• Contributing to best practices across the machine learning lifecycle

Your Skills & Experience

• Strong commercial experience building predictive machine learning models
• Experience deploying models into production environments
• Strong Python skills with experience using machine learning libraries such as scikit-learn
• Experience solving business problems through statistical modeling and machine learning
• Ability to communicate technical findings to non-technical stakeholders
• A practical, delivery-focused approach to data science

The following would be advantageous:

• Experience in credit risk, lending, insurance, or related domains
• Experience developing models that predict customer, risk, or business outcomes
• Familiarity with gradient boosting techniques and modern model development workflows

What They Offer

• 20% annual bonus
• Equity participation
• Fully remote working
• Strong ownership of high-impact machine learning initiatives
• Exposure to business-critical decision-making
• Opportunities for long-term career growth within a mature data science function

Please note: this role is targeted toward Data Scientists with experience developing and owning predictive machine learning models. Candidates whose background is primarily in AI Engineering, MLOps, LLMs, Generative AI, or machine learning infrastructure may not be aligned with the core requirements of this position.