Machine Learning Scientist, Pricing/Personalization (Open to Remote)

About the Opportunity:

The Data Science team is seeking two Machine Learning Scientists to develop and enhance machine learning products that improve understanding of demand, strategy setting, and reader-book connections. The role focuses on building models for either book recommendation or market pricing. These systems support digital discovery, marketing, revenue optimization, and risk mitigation.

Responsibilities:

• Own the ML lifecycle: problem framing, prototyping, validation, and iteration based on feedback

• Apply statistical and ML best practices for feature development, training, evaluation, validation, and maintenance

• Define success metrics; use offline evaluation and online experiments including A/B testing to validate performance and monitor quality

• Collaborate with engineering and platform teams to productionize models, including training, deployment workflows, monitoring, and refresh strategies

• Diagnose model performance and data quality issues; communicate findings and recommendations clearly to stakeholders

• Write maintainable, production-quality code; contribute to team standards including code review, documentation, reproducibility, and testing

• Stay current on applied ML and utilize modern AI tools to accelerate development without compromising quality

Requirements:

• Master’s with 2 years of applied experience or PhD in Computer Science, Machine Learning, Engineering, Operations Research, Statistics, or related quantitative field

• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow

• Strong SQL skills; experience with large datasets for feature development, analysis, and validation

• Experience deploying models to production via batch scoring, APIs, or downstream integration

• Solid understanding of experimentation and measurement

• Ability to use the latest AI tools to develop robust software

• Strong communication skills with the ability to translate between business goals and technical solutions

• Familiarity with cloud and modern data/ML tooling (e.g., AWS, Databricks, Docker, Kubernetes, Spark)

• Exposure to MLOps concepts and tools including model registries, pipelines, monitoring, and reproducibility

Preferred Qualifications:

Forecasting

• Experience with time series forecasting, causal or market-response modeling, optimization, or risk-aware modeling

• Familiarity with automated model retraining, monitoring, and long-term model maintenance

Personalization

• Experience with recommender systems, ranking/retrieval, personalization, segmentation, propensity modeling, or targeting

• Familiarity with experimentation, measurement, and online evaluation

Benefits & Perks:

• Medical and prescription drug insurance

• Dental and vision coverage

• Health Care/Dependent Care Flexible Spending Account

• Health Savings Account

• Pre-Tax and Roth 401(k) plans

• Short and Long-Term Disability Insurance

• Life and AD&D Insurance

• Commuter benefits

• Student Loan Repayment Program

• Educational assistance

• Generous paid time off

Compensation:

• Salary range: $130,000 to $175,000

• Eligibility for annual profit award or bonus subject to company results

Note:

RemoteHunter is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.