Full job description Love what you do. It’s a core value that drives us. At Brad’s Deals, we believe people do their best work where they feel most comfortable, which is why we're proudly remote-first and committed to work-life integration. About Brad’s Deals Our Story - Founded by Brad in 2001, our mission is to help people develop smarter shopping habits. Each year, we feature deals from 800+ retailers and have helped online shoppers save over $225 million. Our Why - We believe there is a better way to shop. It goes beyond price. It's the value in connecting with consumers on what's important so we can deliver the best savings and choices every day. Our Team - We're real people, really helping. We have the passion, creativity, and expertise to create the consumer advantage. Our culture embraces diversity with different talents, experiences, and backgrounds that help us be exceptional together. Our Promise - Consumers first, always. Your Role We are seeking a highly skilled Data Scientist to lead the development and optimization of our personalization and recommendation systems, which power deal delivery to over one million users daily. This role combines hands-on technical implementation with strategic oversight of machine learning initiatives that drive engagement, retention, and revenue growth. The ideal candidate will have experience designing, deploying, and scaling personalization and predictive models in production environments. You will manage end-to-end data science workflows—from experimentation and feature engineering to deployment, monitoring, and continuous improvement of algorithms. You will also collaborate closely with engineering, marketing, and product teams to ensure that our personalization strategy aligns with both user experience and business objectives. This is a high-impact role where you will directly shape how Brad’s Deals surfaces the most relevant and high-value content to every user, every day. What You'll Do Personalization Algorithm Development Design, train, and optimize recommendation and personalization models to deliver relevant daily deals. Monitor and manage model performance in production to ensure scalability, accuracy, and real-time responsiveness. Continuously refine algorithms using user feedback, behavioral data, and A/B testing insights. Data Science & Machine Learning Build robust pipelines for data collection, cleaning, and feature engineering across user, deal, and engagement datasets. Experiment with supervised and unsupervised learning methods to uncover new personalization and ranking opportunities. Develop reproducible modeling frameworks with version control and CI/CD practices in Python and GitHub. Create predictive models for user segmentation, lifetime value (LTV), churn, and engagement likelihood. Integrate lifecycle models with personalization and marketing systems to enhance retention and reactivation strategies. Cross-Functional Collaboration Partner with product, engineering, finance, and marketing teams to embed data science outputs into customer experiences. Translate complex analyses into actionable insights for leadership and stakeholders. Lead experimentation design and metric selection for personalization-focused A/B tests. Collaborate with Paid Acquisition and CRM teams to apply predictive models for audience targeting, budget optimization, and LTV-based bidding. Infrastructure & Data Operations Use Snowflake SQL for large-scale data analysis and model input preparation. Work efficiently in a command-line environment and contribute to shared data science infrastructure. What You'll Bring Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field. 5+ years of experience building and deploying machine learning models in a production environment. Strong proficiency in Python, GitHub, Snowflake SQL, and command line tools. Proven track record with personalization, recommendation systems, or ranking models at scale. Deep understanding of ML lifecycle management, from model training to evaluation and monitoring. Experience with data visualization, experimentation, and performance reporting. Preferred Qualifications: Experience in e-commerce, consumer marketplaces, or content recommendation environments. Familiarity with tools such as Airflow, MLflow, or other workflow orchestration frameworks. Exposure to cloud environments (AWS, GCP, or Azure). Knowledge of reinforcement learning or contextual bandits for personalization. Experience mentoring other data scientists or analysts. If you want to challenge the ordinary and love what you do please consider applying for this great opportunity to join the Brad's Deals team! We offer health benefits (including a no cost medical plan option for individual coverage), regular 401(k) profit sharing contributions, generous paid time off programs, and fun virtual events and activities too. The salary for this position is expected in the $130,000 to $150,000 range (based on candidate's experience and geographic location) with bonus potential. Equal Opportunity Employer / We participate in E-Verify