Product Data Scientist

About the position

We are seeking a skilled and motivated Data Scientist to join our team, focusing on building and implementing advanced models for our MarTech product that increases the ROI of email campaigns by enhancing deliverability. The ideal candidate will have a passion for working with large data sets to identify trends, uncover opportunities, and drive the application of data science techniques that can be efficiently integrated into production environments. This role involves collaborating closely with product teams, working under the guidance of the SVP of Product, and maintaining compliance through regular coordination with the legal team.

Responsibilities

• Build and prototype analysis pipelines iteratively to provide insights at scale by leveraging comprehensive knowledge of data structures and metrics.
• Work cross-functionally to build and communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences inside the Validity product suite.
• Develop end-to-end solutions: identify data sources, develop API & ETL processes to generate production-ready datasets, perform data validation, and build dashboards.
• Serve as an automation solutions architect: develop a framework for connecting and aggregating disparate data efficiently; streamline processes to ensure quick/real-time reporting to internal and external stakeholders; create reusable templates that can be used to support dashboard design and delivery.
• Develop and integrate internal and external client-facing reporting to ensure relevant metrics and insights are shown and understood.
• Analyze and explore large data sets to identify meaningful trends, insights, and opportunities for data science applications within the MarTech domain, particularly in email deliverability.
• Design, build, and optimize predictive and prescriptive models to increase customers' revenue generation via improved email deliverability rates and overall email campaign performance.
• Collaborate with product teams to integrate models into customer-facing products, ensuring seamless user experiences.
• Develop scalable solutions for deploying models into production, including maintaining model performance and reliability.
• Work closely with the legal team to ensure all data science practices comply with industry regulations, data privacy laws, and company policies.
• Contribute to the creation of product roadmaps by sharing insights and advising on potential data-driven solutions.
• Stay up-to-date with industry trends and new technologies to keep the data science strategy current and effective.

Requirements

• 3-5 years of experience in data science roles, with a focus on building production-grade models.
• Strong experience with Python, R, or similar programming languages.
• Proficiency in machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
• Advanced SQL skills for data querying and manipulation.
• Familiarity with cloud-based environments and tools (e.g., AWS, GCP, or Azure) for model deployment.
• Proven ability to work with large data sets to perform exploration and identify actionable insights.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn) for presenting findings effectively.
• Hands-on experience in building, testing, and deploying machine learning models in production.
• Knowledge of machine learning operations (MLOps) practices and tools for model monitoring and maintenance.
• Extensive experience solving analytical problems using quantitative approaches including Machine Learning, Statistical Modeling, Forecasting, Econometrics or other related fields.
• Excellent communication skills for working effectively with product managers, engineers, and cross-functional teams.
• Strong problem-solving skills and an analytical mindset with a keen ability to adapt solutions to changing business needs.

Nice-to-haves

• Bachelor's degree or Master's degree in Data Science, Computer Science, Statistics, or a related field.
• Understanding email marketing metrics, challenges, and optimization techniques is a plus.

Benefits

• Competitive salary
• Health insurance
• Flexible work environment
• Professional development opportunities
• Paid time off