Apple on cord

Apple

Machine Learning Data Scientist

External position
London, UK
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Manufacturing
Make a difference in people’s lives. Including your own.
Posted
a week ago
Checked
cord regularly checks that external positions are still open
2 days ago

Skills & Experience

Job roles: Data Scientist
Experience level: Senior
Core skills considered: Artificial Intelligence, Machine Learning, Python, SQL
Other skills considered: Data Analysis, Data Modeling, Data Pipelines, Deep Learning

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: Hybrid
Visa sponsorship: Not available

Job Description

We are looking for an experienced Data Scientist with the intellectual curiosity and strategic depth to reimagine how Apple Pay measures and optimizes its marketing. You don't wait to be handed a question - you identify the questions worth asking, conceptualize the right framework to answer them, and propose approaches that others haven't considered yet.

You know the marketing and media landscape deeply: how marketing mix models quantify cross-channel marketing effectiveness using statistical or econometrics models, how incrementality testing - from geo-based experiments to causal inference methods - isolates true causal lift, and how behavioral signals derived from clustering, propensity modeling, or sequence analysis can shape smarter audience strategies and campaign design. What sets you apart is the ability to architect the right measurement framework before a single model is built - identifying the causal assumptions that need to hold, the confounders that need to be controlled for, and the experimental conditions that will make results actionable.

AI/ML is the tool you bring to take those frameworks to a level of rigor, scale, and speed that wouldn't otherwise be possible - whether that means building production-grade causal inference pipelines, designing ML-powered experiment analysis, or applying LLMs to accelerate how insights are generated and communicated.


Responsibilities

  • Design and implement marketing mix models and causal inference pipelines that quantify marketing effectiveness and inform budget allocation decisions
  • Build and execute incrementality tests and translate results into concrete campaign recommendations
  • Apply ML techniques such as segmentation, propensity modeling, and behavioral pattern recognition to identify customer response patterns and inform audience strategy and experiment design
  • Partner with cross-functional teams to scope analytical problems, define success metrics, and deliver data-driven recommendations
  • Build and maintain production-grade ML models and workflows that support ongoing marketing measurement and optimization
  • Leverage Generative AI and LLM-based tools to accelerate insight generation, automate reporting workflows, and streamline day-to-day analytical tasks
  • Communicate model outputs and experiment results clearly to both technical and non-technical audiences through visualizations, narratives, and recommendations

Minimum Qualifications

  • Hands-on experience in marketing science - including building marketing mix models, causal inference, and incrementality measurement
  • Experience designing and executing marketing experiments
  • Proficiency in applying ML techniques to marketing and customer datasets
  • Strong proficiency in Python and data science libraries (pandas, NumPy, scikit-learn, statsmodels, or equivalent)
  • Strong command of SQL for querying and analyzing large-scale marketing and media datasets

Preferred Qualifications

  • Experience with paid media data across channels - paid digital, in-store media, social, and other performance marketing platforms
  • Experience with awareness and performance marketing measurement
  • Actively follows industry trends in marketing science and media measurement - aware of emerging methodologies and tools and brings those perspectives into the team
  • Experience applying Generative AI to marketing workflows - including budget optimization, automated creative analysis, or campaign performance reporting
  • Advanced degree (M.S. or Ph.D.) in Statistics, Machine Learning, Econometric, Marketing Science, or a related quantitative field
  • Strong written and verbal communication skills - able to tell compelling stories with data to both technical and non-technical audiences
Machine Learning Data Scientist at Apple
Position posted a week ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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