Lead Data Scientist in United

Energy Jobline ZR; United (WV); À distance; USD 180 000 - 220 000; Plein temps

Avantages offerts par ce poste

Bonus + Equity

Full benefits package

Fully Remote (US)

Résumé du poste

Energy Jobline ZR is partnering with a consumer lending fintech to hire a Principal Data Scientist focused on collections and operations. The role is fully remote in the US, offering up to $200,000 base, bonus and equity, and a strong emphasis on production-grade ML and scalable frameworks.

You will set the modelling standard, drive the roadmap day-to-day, and be the technical reference for data scientists, consultants, and contractors. This is a hands-on IC role, not a people-manager position.

Qualifications

• 7+ years' data science experience or equivalent
• Proven production deployment of ML models
• Strong software engineering habits and reproducibility
• Experience leading technically complex projects
• Fintech, lending, risk, or large-scale modelling exposure beneficial

Responsabilités

• Drive execution of the collections data science roadmap
• Act as lead technical authority across modelling initiatives
• Build models predicting customer response, engagement and repayment
• Influence contact strategies across channels
• Establish scalable modelling and experimentation frameworks
• Raise engineering and production standards across the team
• Reduce reliance on external consultancies by building internal capabilities

Connaissances

Data Science

Production ML

Model monitoring

Stakeholder influence

Senior IC

Formation

Advanced degree in a quantitative field

Outils

Python

Scikit-Learn

LightGBM

Airflow

Kubernetes

Google Cloud Platform

MLflow

BentoML

Chalk Feature Store

DVC

Description du poste

Job Description

Lead Data Scientist - Collections & Operations

US (Remote)

Up to $200,000

I'm partnered with a well-funded consumer lending fintech looking for a Principal Data Scientist to become the technical lead for a highly visible machine learning function focused on customer operations and collections strategy.

This isn't a people management role disguised as a technical one.

You'd be the person setting the modelling standard, driving the roadmap day-to-day, and acting as the technical point of reference for internal Data Scientists, external consultants and specialist contractors.

Why this role is interesting

Most collections organisations have spent years optimising what action to take.

Far fewer have solved how different customers respond to different interventions.

Some engage immediately via SMS. Others respond to email campaigns. Others require a completely different approach.

Understanding those behavioural signals and translating them into production-grade decisioning models remains a surprisingly open problem and one of the core challenges this team is tackling.

You'd be joining at a point where the organisation has meaningful scale, strong funding and large volumes of customer interaction data, but where the collections data science capability is still evolving.

For the right person, there's genuine opportunity to shape what the function looks like over the next several years.

What you'll be responsible for

• Driving execution of the collections data science roadmap
• Acting as the lead technical authority across modelling initiatives
• Building ML models that predict customer response, engagement and repayment behaviours
• Influencing how and when customers are contacted across different channels
• Establishing scalable modelling and experimentation frameworks
• Raising engineering and production standards across the wider team
• Reducing reliance on external consultancies by building durable internal capabilities

Tech Environment

The team operates within a modern ML stack including:

• Python
• Scikit-Learn
• LightGBM
• Airflow
• Kubernetes
• Google Cloud Platform
• MLflow
• BentoML
• Chalk Feature Store
• DVC

Strong interest in MLOps and production machine learning is viewed very positively.

What they're looking for

• 7+ years' commercial Data Science experience (or equivalent advanced academic background)
• Proven experience deploying and monitoring machine learning models in production
• Strong software engineering habits including testing, code review and reproducibility
• Experience leading technically complex projects and influencing senior stakeholders
• Comfortable operating as the most senior individual contributor on a workstream
• Experience within fintech, lending, risk, operations, marketing science or other large-scale predictive modelling environments

Previous collections experience would help but is not required.

Package

Up to $200,000 base

Bonus + Equity

Full benefits package

Fully Remote (US)