Lead Data Scientist - Data Cloud Acceleration

Zeta Global; City Of London; Hybrid; GBP 75,000 - 85,000; Full time

Job summary

A leading marketing technology firm in London seeks a Machine Learning Engineer to prototype data models and manage the ML product lifecycle. The ideal candidate has strong Python skills and experience with machine learning frameworks. You will work in a hybrid capacity with a focus on measurable business results and rapid deployment of solutions.

Benefits

Flexible work environment

Work on diverse projects

Opportunity for rapid impact

Qualifications

• Experience in end-to-end ML product ownership from prototype to service.
• Fluent in Python with machine-learning libraries like Scikit-learn and TensorFlow.
• Solid grounding in statistics and experimental design.

Responsibilities

• Translate fuzzy growth ideas into clear, actionable experiments.
• Prototype models and deploy via APIs or microservices.
• Monitor performance and iterate based on evidence.

Skills

Machine Learning

Python

Statistics

Data Analysis

Tools

Scikit-learn

TensorFlow

SQL

Job description

Overview

WHO WE ARE
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. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

About the team
We're a small band of business savvy technologists who treat machine learning as a means, not an end. Our charter: find revenue shaping opportunities, ship the first working model or service in days or weeks, watch how the market reacts, then double down-or pivot-fast. Ego takes a back seat to curiosity, and "good enough for now" often beats "perfect but late."

What you'll do

• Frame & focus. Translate fuzzy growth ideas into moldeable problems, pick the metrics that matter, and design bite-sized experiments to learn quickly.
• Build fast, in or out of the box. Finetune a foundation model when it's the 80percent solution; spin up a from scratch architecture only when the use case truly needs it.
• Own the full lifecycle. Prototype in notebooks, productionize via Python APIs or lightweight microservices, and wire up offline scoring, real-time inference, and monitoring.
• Make it self-serve. Wrap models in simple endpoints, SDKs, or SQL functions so analysts and engineers can self select the magic without a helpdesk ticket.
• Instrument & iterate. Track performance drift, cost, and business lift; retrain or retire ruthlessly based on evidence.
• Teach the village. Run demos, share code snippets, and mentor teammates on pragmatic ML patterns that survive first contact with customers.

Preferred experience (great to have, but not required)

• End to end ML product ownership-from prototype notebook to cloud native service
• Fluency in Python with libraries such as scikitlearn, PyTorch, TensorFlow, XGBoost, LightGBM
• Experience choosing and finetuning foundation/LLM or diffusion models when they're the quickest path to value
• Comfort with feature stores, vector databases, and MLOps stacks (Airflow/Prefect, MLflow, Kubeflow, SageMaker, Vertex, or equivalents)
• Both batch and low latency serving patterns (REST, gRPC, or streaming)
• SQL that hunts for signal in messy data and A/B results
• Solid grounding in statistics and experimental design, plus the storytelling chops to explain lift to non-data partners
• Version control, CI/CD, and a bias toward shipping thin vertical slices over monoliths

You'll thrive here if you...

• Think "impact > model elegance." You pick the simplest approach that moves the KPI.
• Prototype loudly. You'd rather show a working demo than a 40page deck.
• Stay humble. If a spreadsheet baseline wins, you celebrate-and then raise the bar.
• Translate effortlessly. You can chat GPU kernels at noon and revenue funnels at 12:05.
• Love ambiguity. Blank whiteboards signal possibility, not paralysis.

Why join Zeta's Data Cloud Acceleration team

• Velocity. Your models meet customers in weeks, not quarters.
• Tool freedom. Choose the stack that fits the problem-no six month procurement saga.
• Breadth. Projects jump from ad-tech optimization to identity resolution to GenAIpowered personalization.
• Colleagues who get it. Sharp minds, low egos, and a shared hunger for measurable business results.
• Global flexibility. Work where you think best-our culture is built for distributed teams.

This is a hybrid role based out of our London, UK office.

Salary

SALARY RANGE
The salary range for this role is 75,000 - 85,000 GBP, depending on location and experience.

People & Culture at Zeta

PEOPLE & CULTURE AT ZETA
Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual's sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.

We're committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here: https://zetaglobal.com/blog/a-look-into-zetas-ergs/

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases

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