Senior Data Scientist (Contract)

*Applicants need to be local to the Minneapolis/Twin Cities area of Minnesota. 

RBA is a trusted consulting partner helping enterprise and mid-sized organizations transform their businesses through modern technology solutions. We blend strategic thinking with deep technical expertise to deliver scalable, high-impact outcomes aligned to our clients’ goals. Our team partners with some of the most recognized companies in our market, while fostering a culture that values collaboration, growth, and meaningful work. 

We are seeking a Senior Data Scientist (Analytics & Personalization) to lead the design, development, and deployment of advanced analytics, machine learning models, and data products that power personalization, audience growth, and revenue optimization across channels. 

In this role, you will partner closely with data engineering, product, marketing, and newsroom teams to transform rich behavioral and content data into actionable insights, predictive models, and experimentation frameworks that shape the future of local media experiences.  

What you’ll do

• Design, build, and deploy predictive models and machine-learning algorithms using Python and SQL on our Snowflake data platform to drive audience growth, retention, and monetization. 

• Analyze large-scale structured and unstructured datasets (content, subscriber, advertising, engagement, and campaign data) to identify trends, patterns, and opportunities for personalization and product optimization. 

• Develop, validate, and maintain propensity models (e.g., churn, subscription upgrade, engagement scoring) and recommendation systems that personalize content and offers across web, mobile, email, and push notification channels. 

• Partner with Data Engineers to define robust data requirements, feature stores, and analytical datasets; ensure data pipelines, schemas, and governance practices support high-quality modeling and experimentation. 

• Design and execute A/B tests and other experimental frameworks to measure the impact of personalization strategies, product changes, and marketing initiatives; interpret results and translate them into clear recommendations. 

• Build scalable analytical tools, dashboards, and reports that provide clear visibility into key KPIs (engagement, conversion, churn, campaign performance) for business stakeholders and leadership. 

• Perform rigorous model monitoring, performance tracking, and error analysis to improve model accuracy and reliability; implement alerting and retraining strategies to keep models current. 

• Use modern MLOps practices and CI/CD pipelines to automate model deployment, versioning, and lifecycle management in production environments. 

• Act as a player-coach, mentoring junior data scientists and analysts on modeling best practices, code quality, and effective communication with business stakeholders. 

• Champion a quantitative, experiment-driven culture, encouraging data-informed decision making across product, newsroom, marketing, and advertising teams. 

• Partner closely with Data Engineers to maintain high data quality, consistent definitions, and trusted data products that underpin analytics and AI solutions. 

• Demonstrate a problem-solving mindset focused on scalable, automated solutions rather than manual, one-off analyses. 

• Communicate complex technical concepts simply and clearly, adapting your message for executives, editors, marketers, and technical peers. 

• Collaborate with product, marketing, and newsroom teams to frame business questions, translate them into analytical approaches, and communicate results through compelling narratives, visualizations, and recommendations. 

• Stay current with advances in machine learning, AI, and media analytics, bringing new techniques and tools into our Data & AI stack where they add clear business value. 

What you bring

• 5+ years of professional experience in data science, applied statistics, or machine learning, including building and deploying models in production environments. 

• Strong proficiency in Python (e.g., pandas, NumPy, scikit-learn, PyTorch or TensorFlow) and SQL, with the ability to work efficiently in distributed cloud data platforms such as Snowflake. 

• Hands-on experience designing and evaluating predictive models, recommendation engines, and segmentation frameworks using statistical and machine learning techniques. 

• Solid understanding of experimental design, A/B testing, and causal inference concepts, with experience applying them to digital products or marketing campaigns. 

• Experience working with modern data workflows and tooling, such as Airflow for orchestration, dbt for transformations, and version-controlled codebases (Git). 

• Ability to work with large, complex datasets, including data cleaning, feature engineering, and data quality assessment. 

• Strong data visualization and storytelling skills using tools such as Tableau, Power BI, or Python visualization libraries, with a focus on clarity for non-technical audiences. 

Nice to have 

• Experience in media, publishing, or subscription-based businesses, particularly in personalization, audience analytics, or ad-tech contexts. 

• Familiarity with Snowflake advanced features (Streams, Tasks, Snowpipe, Snowpark) and building model-serving or analytics applications on top of Snowflake. 

• Background in natural language processing or recommender systems applied to content discovery and user engagement. 

• Experience with MLOps platforms and practices (model registries, monitoring, automated retraining) in cloud environments. 

• Advanced degree in statistics, computer science, data science, applied mathematics, or a related quantitative field.