Product Data Scientist

February 15

⛰️ Colorado – Remote

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🦌 Connecticut – Remote

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+11 more states

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⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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Logo of Validity Inc.

Validity Inc.

Businesses run better and grow faster with trustworthy data. Tens of thousands of organizations across the world rely on Validity solutions – including Everest, DemandTools, BriteVerify, GridBuddy Connect, and MailCharts – to target, contact, engage, and retain customers effectively. Marketing, sales, and customer success teams worldwide trust Validity solutions to help them create smarter campaigns, generate leads, drive response, and increase revenue.

CRM • Data Validation • Salesforce • Deduplication • Software-as-a-Service

201 - 500 employees

📋 Description

• We are hiring for an experienced Senior Product Data Scientist/Product Data Scientist with a minimum of 3-years directly-related SaaS industry experience 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. • 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 at the Senior Data Scientist or Data Scientist level, 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. • Experience working closely with legal or compliance teams to align data science practices with regulatory requirements. • Strong problem-solving skills and an analytical mindset with a keen ability to adapt solutions to changing business needs. • A scientifically rigorous approach to analysis and data, and a well-tuned sense of skepticism, attention to detail and commitment to high-quality, results-oriented output.

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