Senior Data Scientist — Data Cloud Acceleration
Level inferred from job title
Job description
The Senior Data Scientist builds models, analyses, and supporting ML components that improve business decisions, intelligence products, and client outcomes. This is a hands-on individual contributor role owning defined deliverables from requirement understanding through modeling, validation, documentation, and delivery.
At a glance
- Work mode
- Remote
What you'll do
- Own model and analysis deliverables, independently delivering a reliable model, analysis component, scoring workflow, or supporting dataset
- Translate business questions into analytical approaches, asking clarifying questions and recommending an approach that fits the decision, timeline, and available data
- Build and test models quickly using statistical methods, machine learning, deep learning, or existing models and services
- Prepare trustworthy data by profiling, cleansing, joining, and validating noisy datasets, checking completeness, freshness, distributions, nulls, duplicates, and match rates
- Create repeatable scoring workflows by building reusable Python components, batch-scoring processes, APIs, or lightweight services
- Evaluate results responsibly by establishing baselines, selecting appropriate metrics, performing statistical reasonableness checks, reconciling unexpected results, and documenting limitations
- Support intelligence products and applications by working with application and data teams to define data ingredients, test hypotheses, and integrate model outputs
- Add operational discipline including validation, monitoring, failure handling, refresh expectations, documentation, and a clear usage path
- Use AI tools such as Claude, Codex, and similar assistants to accelerate coding, testing, research, debugging, and documentation while independently verifying results
- Communicate progress early and clearly, making milestones, assumptions, risks, dependencies, and issues visible
What we're looking for
- Experience applying statistical analysis and machine learning to real business problems
- Strong Python skills and familiarity with libraries such as pandas, scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow
- Strong SQL skills and experience analyzing large datasets
- Experience with cloud data platforms such as Snowflake, Databricks, Athena, Hive, BigQuery, or similar technologies
- Experience developing classification, regression, clustering, forecasting, recommendation, optimization, or anomaly-detection solutions
- Familiarity with model evaluation, experimental design, feature engineering, and statistical validation
- Experience creating repeatable batch-scoring workflows or exposing model outputs through APIs or services
- Familiarity with orchestration and automation tools such as Airflow, AWS Glue, Prefect, or similar platforms
- Experience using version control, testing, and reproducible development practices
- Ability to explain analytical results and trade-offs to technical and nontechnical stakeholders
- Meaningful use of GenAI tools to improve the speed and quality of day-to-day work
Your team
Data Cloud Acceleration
Identifies gaps and opportunities across clients and business units, then moves quickly to deliver practical new capabilities. Often develops and deploys the first version of a model, workflow, dataset, or application in days or weeks, learns from real usage, and improves it iteratively. Business-minded technologists who care more about impact than technical novelty.
Benefits
- Excellent medical, dental, and vision coverage
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About Zeta Global
The AI-Powered Marketing Cloud
Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry's largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs.
Mission
To make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform.
Key facts
- 2007
- New York City
- NYSE: ZETA
- Founded in 2007 by David A. Steinberg and John Sculley
- Headquartered in New York City with offices around the world
- Powered by one of the industry's largest proprietary databases and AI
What they value
- Trust and belonging
- Diversity, equity and inclusion