Product Data Scientist - MARTECH

March 5

⛰️ Colorado – Remote

Although this job is listed in Colorado, this company may be open to hiring remote in other states.

🦌 Connecticut – Remote

Although this job is listed in Connecticut, this company may be open to hiring remote in other states.

+11 more states

⛰️ Colorado – Remote 🦌 Connecticut – Remote 🐊 Florida – Remote 🌽 Illinois – Remote 🦞 Maine – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote 🍂 Massachusetts – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🤠 Texas – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

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Validity Inc.

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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

• Hiring an experienced Senior Data Scientist/Product Data Scientist to focus on building and implementing advanced models for MarTech product. • Collaborate closely with product teams and maintain 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, collaborating closely with product managers, engineers, designers, and researchers. • Develop end-to-end solutions, including identifying data sources and designing production-ready datasets. • Serve as an automation solutions architect to streamline processes and create reusable templates for dashboard design. • Develop and integrate internal and external client-facing reporting to ensure relevant metrics and insights are shown and understood. • Design, build, and optimize predictive and prescriptive models to increase customers’ revenue through improved email deliverability rates. • Collaborate with product teams to integrate models into customer-facing products for seamless user experiences. • Develop scalable solutions for deploying models into production, maintaining performance and reliability.

🎯 Requirements

• 3-5 years of experience in data science roles at the Senior Data Scientist/Product 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. • Ability to manipulate large data sets with high dimensionality and complexity. • 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.