Lead Data Scientist

About the role

Cadent ignites seamless connections between brands, publishers, and consumers. Our predictive AI orchestrates outcomes on any platform customers are on, across any media they consume, and at any stage of the journey. We are looking for a highly motivated and experienced Lead Data Scientist within the Data Services Organization to shape our data science strategy, manage a team of data scientists, deliver ML products, and collaborate with cross-functional teams to translate data into actionable business strategies.

This role applies scientific methods to identify business optimization strategies and develop, evaluate, and demonstrate prototypes and production-grade builds. The Lead Data Scientist will collaborate directly with Business, Product, Data Engineering, DevOps, and QA teams to productize AI/ML research and drive business growth. Output from this role will be leveraged by business teams, engineers, and senior executives to define the future of Cadent.

Responsibilities

• Shape and execute data science strategy, managing a team of data scientists to deliver ML products.
• Develop, evaluate, and deploy prototypes and production-grade machine learning models.
• Work with LLM technologies, including generative and embedding techniques, modern model architectures, retrieval-augmented generation (RAG), fine-tuning/pre-training LLMs (including parameter-efficient fine-tuning), and evaluation benchmarks.
• Answer open-ended research questions using data, tools, and technology.
• Write clean, expressive code in Python using open-source frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and tools like PySpark and Scala.
• Use SQL and relational databases, and leverage cloud computing ecosystems (e.g., AWS, GCP).
• Apply computational statistics and complex ML algorithms, including deep learning, GraphDB, SVMs, and time-series forecasting, to build and evaluate models.
• Deploy models in production and enable model governance.
• Communicate technical concepts and insights to non-technical stakeholders, influencing decision-making across the organization.
• Oversee the end-to-end lifecycle of data science projects, from problem formulation to model deployment and monitoring.
• Define project scope, objectives, and success metrics, ensuring projects are delivered on time and within budget.
• Present results and findings to technical, product, and business stakeholders.
• Innovate using the latest algorithms, tools, and systems while staying abreast of industry trends and best practices in data science.
• Research new data, tools, algorithms, and tech stacks to align with evolving AI and ML industry standards.
• Collaborate with machine learning engineers, data engineers, DevOps, and software developers to deploy models and modeling pipelines.
• Align with Product and business teams on deliverables and timelines, providing progress updates.
• Foster a collaborative and innovative team culture that encourages knowledge sharing and continuous learning.
• Participate in Agile/Scrum processes and follow the CRISP-DM process for robust documentation.
• Collaborate with the broader Data Services group, including Machine Learning Engineers, Data Engineers, Analytics Engineers, Software Engineers, Quality Assurance Engineers, and Business Intelligence analysts.

Requirements

• M.S. or higher in computer science, mathematics, operations research, statistics, or a related discipline with a focus on machine learning; or 6-7 years of equivalent experience in a Data Science and Machine Learning role.
• 6+ years of hands-on data science and machine learning development experience.
• Hands-on design, training, and application of statistics, mathematical models, and machine learning techniques to create scalable ML solutions (e.g., identity resolution) for business problems.
• Contribute iterative improvements to predictive models using the latest ML techniques and algorithms.
• Leverage model governance techniques to ensure performance and stability of data science products.
• Fundamental understanding of the mathematical workings of standard feature engineering, dimension reduction, machine learning algorithms, and model validation and measurement.
• Familiarity with best practices for software engineering and the scientific Python ecosystem.
• Media or ad-tech experience is a plus.

Must be legally authorized to work in the United States without employer sponsorship now or in the future.

Benefits

Health & Wellbeing

• Inclusive health, dental, and vision plans built to support diverse lifestyles.
• Enhanced support for reproductive health, family planning, and new parents.
• Employer contribution to HSA.
• Voluntary benefits: Pet Insurance, LegalEase Legal Assistance, Critical Illness, Hospital Indemnity, and Accident coverages.
• Generous and inclusive paid parental leave.
• Mental health support and Employee Assistance Program (EAP).
• Free access to the Calm App.
• Monthly Wellness reimbursement.
• Special discounts through LifeMart and Plum Benefits.
• Flexible Time Off (FTO) policy and company breaks.
• 11 observed Federal holidays.
• Summer Fridays between Memorial Day and Labor Day.

Inclusion & Belonging

• Employee Resource Groups that foster connection and community.
• DEI programming and initiatives.
• Company-sponsored events to bring employees together.
• Offices across the U.S., including Manhattan, Philadelphia, and San Jose.

Financial & Security

• 401(k) participation with discretionary employer match.
• Life, Short-term, and Long-term Disability coverage.
• Cell phone and WiFi stipend.
• Pre-tax commuter benefits.
• Access to certified financial coaches and planning tools.

Pay

USD $150,000.00 - USD $175,000.00 per year. The salary range for this role takes into account a wide range of factors, including skill sets, experience, training, licensure, certifications, and business and organizational needs.