Product Data Scientist

Validity; Boston (MA); On-site; USD 80,000 - 120,000; Full time

Job summary

Join a dynamic team as a Data Scientist, where your passion for data will drive impactful solutions in the MarTech space. This role offers the opportunity to work with large datasets, develop predictive models, and collaborate closely with product teams to enhance email campaign performance. You will be at the forefront of leveraging data science techniques to improve deliverability and ROI for clients. An innovative firm that values creativity and strategic thinking, Validity fosters a culture of collaboration and continuous learning, making it a great place for professionals eager to make a difference in the data-driven marketing landscape.

Benefits

Flexible working hours

Health insurance

Professional development opportunities

Remote work options

Team-building events

Generous vacation policy

Retirement savings plan

Wellness programs

Casual dress code

Free snacks and beverages

Qualifications

• 3-5 years of experience in data science roles with production-grade models.
• Strong programming skills in Python or R and advanced SQL proficiency.

Responsibilities

• Build analysis pipelines to provide insights at scale using data structures.
• Develop and integrate reporting solutions for internal and external clients.

Skills

Python

R

Machine Learning

SQL

Data Visualization

Cloud Computing (AWS, GCP, Azure)

Data Exploration

MLOps

Statistical Modeling

Collaboration

Education

Bachelor's degree in Data Science

Master's degree in Data Science

Bachelor's degree in Computer Science

Bachelor's degree in Statistics

Tools

Scikit-learn

TensorFlow

PyTorch

Tableau

Power BI

Matplotlib

Seaborn

Job description

About the Role
We are seeking a skilled and motivated Data Scientist with a minimum of 3-years directly related full-time work 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.

Team Dynamic
Product Management at Validity is challenging, high-impact, and rewarding. To be successful, you must have strong business acumen, strategic and analytical thinking skills, and process orientation. Additionally, you should be a champion for positive impact and be ready to tackle day-to-day problems with humility and humor.

Position Duties and Responsibilities

1. Build and prototype analysis pipelines iteratively to provide insights at scale by leveraging comprehensive knowledge of data structures and metrics.
2. 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.
3. Develop end-to-end solutions: identify data sources, develop API & ETL processes to generate production-ready datasets, perform data validation, and build dashboards.
4. 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.
5. Develop and integrate internal and external client-facing reporting to ensure relevant metrics and insights are shown and understood.
6. 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.
7. Design, build, and optimize predictive and prescriptive models to increase customers’ revenue generation via improved email deliverability rates and overall email campaign performance.
8. Collaborate with product teams to integrate models into customer-facing products, ensuring seamless user experiences.
9. Develop scalable solutions for deploying models into production, including maintaining model performance and reliability.
10. Work closely with the legal team to ensure all data science practices comply with industry regulations, data privacy laws, and company policies.
11. Contribute to the creation of product roadmaps by sharing insights and advising on potential data-driven solutions.
12. Stay up-to-date with industry trends and new technologies to keep the data science strategy current and effective.

Required Experience, Skills, and Education

1. Experience:
   1. 3-5 years of experience in data science roles, with a focus on building production-grade models.
2. Technical Proficiency:
   1. Strong experience with Python, R, or similar programming languages.
   2. Proficiency in machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
   3. Advanced SQL skills for data querying and manipulation.
   4. Familiarity with cloud-based environments and tools (e.g., AWS, GCP, or Azure) for model deployment.
3. Data Exploration and Analysis:
   1. Proven ability to work with large data sets to perform exploration and identify actionable insights.
   2. Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn) for presenting findings effectively.
   3. Ability to manipulate large data sets with high dimensionality and complexity.
4. Model Development and Productionalization:
   1. Hands-on experience in building, testing, and deploying machine learning models in production.
   2. Knowledge of machine learning operations (MLOps) practices and tools for model monitoring and maintenance.
   3. Extensive experience solving analytical problems using quantitative approaches including Machine Learning, Statistical Modeling, Forecasting, Econometrics or other related fields.
5. Collaboration & Communication:
   1. Excellent communication skills for working effectively with product managers, engineers, and cross-functional teams.
   2. Experience working closely with legal or compliance teams to align data science practices with regulatory requirements.
6. Problem-Solving:
   1. Strong problem-solving skills and an analytical mindset with a keen ability to adapt solutions to changing business needs.
   2. 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.

Preferred Experience, Skills, and Education

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

About Validity
For over 20 years, tens of thousands of organizations across the world have relied on Validity solutions to target, contact, engage, and retain customers – using trustworthy data as a key advantage. Validity’s flagship products – Everest, DemandTools, BriteVerify, and GridBuddy Connect – are all highly rated, #1 solutions for sales and marketing professionals. These solutions deliver smarter email campaigns, more qualified leads, more productive sales, and ultimately faster growth.

Validity is a truly unique company - massive revenue growth, top-tier investors, 5-star product ratings, proven ability to acquire and integrate top tech companies and welcome them into the Validity family, a winning culture, and a work environment that fosters hard work, trust, and fun.

Headquartered in Boston, Validity has offices in Tampa, Denver, London, Sao Paulo, and Sydney. For more information, connect with us on LinkedIn, Instagram, and Twitter.

Validity is proud to be an equal opportunity employer. We are committed to providing equal employment opportunities to all employees and applicants for employment regardless of actual or perceived race, color, ancestry, national origin, citizenship, religion or creed, age, physical or mental disability, medical condition, AIDs/HIV status, genetic information, military and veteran status, sex, parental status (including pregnancy and pregnancy-related conditions, childbirth, post childbirth, nursing mother, parent of a young child and parent of a foster child), gender (including gender identity and expression), sexual orientation, marital status (including registered domestic partner status), or any other characteristic protected by applicable federal, state, or local law.