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# Software Engineering - Lead Data Scientist

- **Company:** The Ladders
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $138,000.0 - $165,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Amazon Web Services, Big Data, Code Review, Information Engineering, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Software Engineering, Pytorch, Large Language Models, Prompt Engineering, Apache Spark, Generative AI, Pandas, Information Technology, Data Analytics, Xgboost, Machine Learning Operations, Data Pipelines
- **Published:** November 7, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/px8f2j3nac

## About the Role

* 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

## Description

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., * 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