Software Engineering - Lead Data Scientist

Ladders; United States; Remote; USD 138,000 - 165,000; Full time

Benefits offered by this job

Inclusive culture reflecting core data

Professional development opportunities

Competitive compensation and rewards

Work/life balance and collaborative环境

Job summary

Ladders is seeking a Software Engineering - Lead Data Scientist for a remote role focused on building and operationalizing machine learning solutions that scale across the business. You will partner with engineering and cross-functional teams to deliver reliable data pipelines, high data quality, and production-ready models.

Lead design discussions, review code, mentor teammates, and work with modern ML approaches and cloud deployment.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• Strong Python skills for data engineering and ML, including libraries such as pandas and NumPy.
• Experience building data pipelines and processing large datasets with technologies such as Spark or Redshift.
• Hands-on experience with ML frameworks such as XGBoost, TensorFlow, or PyTorch.
• Experience operationalizing ML models in AWS, including deployment and monitoring.
• Familiarity with LLMs and Generative AI solutions, including prompt design and evaluation.
• Strong grounding in statistics and experimental design.

Responsibilities

• Build and maintain Python data pipelines for large datasets.
• Profile and validate data, implementing quality checks to ensure trustworthiness.
• Develop machine learning models from problem framing through evaluation.
• Deploy models to AWS for batch and real-time scoring, while monitoring performance and drift.
• Design and analyze A/B tests to measure business impact and communicate results.
• Lead design discussions, code reviews, and mentor team members.
• Collaborate with cross-functional teams to ensure secure handling of consumer data.

Skills

Python

Pandas/NumPy

ML frameworks

AWS deployment

LLMs / Generative AI

Statistics / experimental design

Education

Bachelor's or Master's in CS/Data Science/Statistics

Tools

Spark

Redshift

Job description

For our client, we are seeking a Software Engineering - Lead Data Scientist to join the team of a leader in the Finance & Insurance space.

This role will focus on building and operationalizing machine learning solutions that support business decision-making and scoring at scale. The Lead Data Scientist will partner closely with engineering and cross-functional stakeholders to deliver reliable data pipelines, strong data quality, and production-ready models. The position also calls for leadership in technical design, code review, experimentation, and mentorship within a collaborative environment. Experience with modern ML, LLMs, and cloud-based deployment will be important as the team advances data-driven capabilities.

Location: Remote

Compensation: $138,000 – $165,000 annually

Responsibilities

• Build and maintain Python data pipelines for large datasets
• Profile and validate data, implementing quality checks to ensure trustworthiness
• Develop machine learning models from problem framing through evaluation
• Deploy models to AWS for batch and real-time scoring, while monitoring performance and drift
• Design and analyze A/B tests to measure business impact and communicate results
• Lead design discussions, code reviews, and mentor team members
• Collaborate with cross-functional teams to ensure secure handling of consumer data

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field
• Strong Python skills for data engineering and ML, including libraries such as pandas and NumPy
• Experience building data pipelines and processing large datasets with technologies such as Spark or Redshift
• Hands-on experience with ML frameworks such as XGBoost, TensorFlow, or PyTorch
• Experience operationalizing ML models in AWS, including deployment and monitoring
• Familiarity with LLMs and Generative AI solutions, including prompt design and evaluation
• Strong grounding in statistics and experimental design

Benefits

• Inclusive culture reflecting core values of ownership, customer delight, and respect
• Opportunities for professional development and leveraging unique strengths
• Highly competitive compensation and rewards programs
• Engaging work environment promoting work/life balance and social interaction

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.