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Bengaluru, Karnataka, India
Onsite
Job Description :
Job Description
Role: Data Scientist
Reporting to: Senior Data Science Manager
Location: Bangalore, India
Background
Who we are
We are Data Tech, a program that comprises a number of agile, cross-functional teams between London, Sofia, and Bangalore. We grow data platforms, build front-end data products, and create predictive models and Gen AI products for News UK. Our users include the newsroom editors, marketing, advertising, and product teams associated with our world-leading digital and print publications. From operations and infrastructure support to data technology and software development, we are committed to finding creative solutions to deliver essential news around the globe. We believe that technology will always be a tool driven by human intent.
About the role
Who we are looking for
We are looking for a Data Scientist to join the home of Data Science within News UK. You will work hands-on across a portfolio of AI and ML products, from LLM-powered editorial tools to personalisation and predictive models that shape what millions of readers see, read, and stay subscribed to.
This is a build-focused role. You will spend most of your time in code: training models, designing and running evaluations, building RAG and LLM features, and shipping work that holds up in production. You will contribute to architecture and design discussions, and grow into owning larger pieces of work over time.
We care as much about how you work as what you build. We are looking for someone who communicates clearly with both technical and non-technical people, who takes the initiative rather than waiting to be told, and who brings solid engineering practices to everything they ship. If you have a genuine interest
in AI, a drive to take sensible risks, and the curiosity to keep learning, this is a great place to do your best work.
Our Current Tech Stack
● Cloud and infrastructure: Google Cloud Platform, Vertex AI, BigQuery, Cloud Run, GCS, Cloud Composer, Cloud Scheduler
● GenAI development: Python, LangChain, LangGraph, Google ADK, Gemini, Claude, Vertex AI RAG Engine, prompt engineering
● Machine learning: scikit-learn, XGBoost / LightGBM, PyTorch, personalisation and recommender approaches, embedding-based retrieval, classical statistical modelling
● MLOps and IaC: Terraform, Cloud Build, Git-based CI/CD, model monitoring and drift detection,
● Evaluation and LLMOps: Custom eval harnesses, LLM-as-judge frameworks, tracing and observability, Braintrust
Duties & Responsibilities
● Build, validate, and ship machine learning models for real business problems such as churn and retention, customer lifetime value, propensity, segmentation, content classification, and forecasting.
● Contribute to the personalisation and recommender systems work, including content discovery, ranking, and the experiments that prove what is working.
● Build production RAG and LLM features on Vertex AI, covering retrieval, prompt engineering, guardrails, and evaluation.
● Help design and run evaluation frameworks for ML and LLM systems, covering offline metrics, A/B testing, and process-level checks for agentic systems.
● Write clean, well-tested Python and contribute to Terraform-managed environments and CI/CD pipelines.
● Explore agentic approaches using Google ADK and similar tooling, and turn promising ideas into working features.
● Keep up with new AI models and methods, and bring ideas to the team proactively.
● Work closely with cross-functional teams, and communicate your work clearly to stakeholders across the newsroom, marketing, and product.
Skills & Competencies
The following skills are essential or desirable.
Essential
● Around 3+ years in data science or applied ML, with hands-on delivery of production work.
● Strong software engineering foundations: clean, well-structured Python, testing, version control with Git, code review, and comfort taking work from notebook to production.
● Hands-on MLOps experience: building and maintaining CI/CD pipelines, containerising and deploying models on Cloud Run, and setting up model monitoring and drift detection.
● Experience with Infrastructure as Code (Terraform preferred) and building reproducible, automated pipelines.
● Confident with GCP, ideally Vertex AI, BigQuery, Cloud Run, GCS, and Cloud Composer.
● Strong SQL for querying and shaping large datasets.
● Hands-on experience across the ML lifecycle, including feature engineering, model selection, training, validation, deployment, and monitoring, for classification, regression, and time-series problems.
● Practical experience with LLMs and Generative AI, including RAG, prompt engineering, and evaluation.
● Strong communication skills, able to explain technical work clearly to non-technical audiences.
● A proactive, self-directed approach, comfortable picking up problems and driving them forward.
Desirable
● Experience building evaluation harnesses and LLMOps tooling, including tracing and observability for LLM and agentic systems.
● Experience with model registries, feature stores, and incident response for ML in production.
● Experience with personalisation or recommender systems. ● Experience with agentic systems and orchestration (Google ADK, LangGraph, or similar).
● Hands-on experience with Gemini and Claude.
● Experience with vector databases and embedding-based retrieval. ● Background in media, publishing, or subscription businesses. ● Familiarity with Agile delivery practices.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status or any other protected characteristic.
Reasonable Accommodation
We are committed to providing reasonable accommodation for qualified individuals with disabilities in our job application and/or interview process. If you need assistance or accommodation in completing your application or participating in an interview due to a disability, email us at humanresources@newscorp.com. Please put "Reasonable Accommodation" in the subject line and provide a brief description of the type of assistance you need. This inbox will not be monitored for application status updates.
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