Sr. Data Scientist, Marketing

About This Role

Lead and execute data science initiatives, developing and deploying advanced AI/ML solutions to drive organic growth and optimization for marketing stakeholders. This role covers the full data lifecycle from data collection to building robust models and serves as a thought leader in the marketing domain.

Responsibilities

• Independently lead the planning and execution of data science initiatives across multiple projects and functional areas
• Mentor and coach junior team members on best practices in model architecture, coding standards, and testing methodologies
• Evaluate and recommend new data sources, tools, and emerging technologies to keep the organization at the forefront of AI/ML innovation
• Define project objectives by translating high-level business goals into concrete technical requirements in collaboration with stakeholders
• Design, develop, and validate robust machine learning models to solve specific business problems
• Apply advanced statistical techniques to perform classification, clustering, hypothesis testing, and predictive analysis
• Conduct rigorous Exploratory Data Analysis (EDA) to identify hidden patterns, anomalies, and trends within large datasets
• Drive experimentation (e.g., A/B testing) to measure the impact of model deployment and marketing strategies
• Architect data pipelines for the collection, cleaning, and preprocessing of complex, high-volume datasets from disparate sources
• Oversee the deployment lifecycle, ensuring models are successfully integrated into production environments and monitored for performance drift
• Maintain engineering excellence by documenting code, methodologies, and results clearly, ensuring reproducibility and scalability
• Transform complex data into clear, actionable insights for non-technical stakeholders using data visualizations, dashboards, and executive reports
• Drive product innovation by contributing directly to the development of data-driven features and marketing optimization tools
• Act as a bridge between technical and non-technical teams, ensuring data solutions align directly with marketing and organic growth KPIs

Requirements

• 8+ years of relevant experience in data analysis, statistical modeling, and machine learning application
• Advanced proficiency in Python or R
• Expert-level knowledge of standard libraries (e.g., Pandas, NumPy, SciPy, Scikit-Learn in Python; dplyr, tidyr, ggplot2 in R)
• Deep understanding of statistical concepts, probability theory, and experimental design (A/B testing, hypothesis testing)
• Extensive experience with ML algorithms, including linear/logistic regression, classification, clustering, dimensionality reduction, and ensemble methods
• Advanced SQL skills with a strong understanding of database architecture and complex query optimization
• Proven ability to handle imperfect data, possessing strong analytical skills to clean, structure, and extract value from noisy or unstructured datasets
• Data Visualization expertise using tools such as Matplotlib, Seaborn, Plotly, or Tableau
• Excellent written and verbal communication, with a specific talent for translating technical findings into business implications for non-technical leadership
• Collaborative mindset with the ability to work independently on complex tasks while coordinating with cross-functional teams
• Growth mindset, demonstrating a continuous passion for learning new technologies

Qualifications

• Bachelors, Master’s or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field
• 8+ years of relevant experience in data analysis, statistical modeling, and machine learning application.

Nice to Have

• Hands-on experience with cloud platforms (AWS, Azure, GCP)
• Hands-on experience with big data technologies (Spark, Hadoop, Databricks)
• Experience using version control (Git) in a team setting
• Experience deploying machine learning models into production environments (Docker, Kubernetes, CI/CD)
• Prior experience in Digital Marketing, Subscription business or home services industry

Skills

* Required skills

Benefits