Data Scientist

Sotalent; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

Sotalent is seeking a Data Scientist to drive product innovation through predictive modeling, recommendation systems, experimentation, and advanced analytics. You will collaborate with Product, Engineering, Growth, Editorial, and Data teams to build intelligent systems that improve user engagement and subscription performance.

You will design and deploy production-ready ML pipelines, analyze large-scale user behavior, and translate findings into actionable business insights while partnering with

Qualifications

• 2-4 years of experience in Data Science or related analytical roles.
• Proven ability to apply statistical methods to real-world business problems using large datasets.
• Strong proficiency in Python for data analysis and model development, plus production deployment.
• Solid SQL skills for querying and managing data warehouses.
• Experience building predictive models and recommendation systems.
• Excellent analytical, problem-solving, and communication skills.

Responsibilities

• Design, develop, and deploy machine learning models that support product objectives.
• Build predictive models to identify users likely to subscribe, retain, or engage with premium content.
• Develop and enhance recommendation engines to deliver content to users at the right time.
• Apply advanced statistical and ML techniques to solve business challenges.

Skills

Python

SQL

Machine Learning

Experimentation

Communication

Education

BSc in CS/Math/Statistics

Job description

Industry: IT Services and IT Consulting

Are you passionate about using machine learning and advanced analytics to shape how millions of sports fans discover content, engage with products, and become loyal subscribers?

We are seeking a Data Scientist to drive product innovation through predictive modeling, recommendation systems, experimentation, and advanced analytics. In this role, you will work closely with Product, Engineering, Growth, Editorial, and Data teams to build intelligent systems that improve user engagement, optimize subscription conversion, and create personalized experiences for sports fans.

Key Responsibilities

• Design, develop, and deploy machine learning models that support key business and product objectives.
• Build predictive models to identify users most likely to subscribe, retain, or engage with premium content.
• Develop and enhance recommendation engines that deliver the right content to the right users at the right time.
• Apply advanced statistical and machine learning techniques to solve complex business challenges.

Analytics & Business Insights

• Analyze large-scale user behavior and content consumption data to uncover actionable insights.
• Use quantitative analysis to understand customer preferences, engagement patterns, and subscription behavior.
• Translate analytical findings into recommendations that improve product performance and user experience.
• Measure the effectiveness of product initiatives, content strategies, and growth programs.
• Design, execute, and evaluate A/B tests and other experimental frameworks.
• Guide complex experimentation efforts to validate product and business hypotheses.
• Partner with Product and Growth teams to optimize acquisition, engagement, retention, and monetization strategies.
• Develop measurement methodologies that support data-driven decision making.

Data Science Engineering

• Design and maintain production-ready data science and machine learning pipelines.
• Build scalable workflows for model training, deployment, monitoring, and optimization.
• Ensure models and data products remain accurate, reliable, and performant in production environments.
• Collaborate with Engineering teams to integrate AI and machine learning solutions into customer-facing products.

Cross-Functional Collaboration

• Partner with Product, Engineering, Growth, Editorial, and Business teams to identify opportunities for innovation.
• Translate complex technical concepts into clear business insights and recommendations.
• Present findings and data-driven stories to both technical and non-technical stakeholders.
• Help cultivate a collaborative, innovative, and high-performing data science culture.

Required Qualifications

• 2-4 years of experience as a Data Scientist, Data Analyst, Machine Learning Engineer, or similar analytical role.
• Proven experience applying scientific and statistical methods to solve real-world business problems using large-scale datasets.
• Strong proficiency in Python for data analysis, machine learning model development, and production deployment.
• Strong SQL skills with experience querying and managing large data warehouse environments.
• Experience developing predictive models and machine learning solutions.
• Solid understanding of statistical concepts and predictive modeling techniques.
• Experience working with user behavior, engagement, or subscription-based analytics.
• Excellent analytical, problem-solving, and critical-thinking skills.
• Strong written and verbal communication abilities.
• Ability to communicate sophisticated concepts to diverse technical and business audiences.

Preferred Qualifications

• Experience with recommendation systems, personalization platforms, or content ranking algorithms.
• Understanding of subscription media, digital publishing, streaming, or consumer-facing digital products.
• Experience with experimentation frameworks, A/B testing, and causal analysis.
• Knowledge of machine learning operations (MLOps) and production model deployment.
• Familiarity with cloud-based data and machine learning platforms.
• Experience working with large-scale web, clickstream, or customer engagement datasets.
• Passion for sports, media, analytics, and consumer product experiences.