At a Glance
- Tasks: Own the entire lifecycle of AI models, from training to deployment in production systems.
- Company: Join a cutting-edge AI team in London focused on innovative solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship opportunities and career advancement.
- Why this job: Make a real impact by bridging traditional methods with next-gen AI technologies.
- Qualifications: Strong experience in AI, ML, and Python; hands-on with LLMs and MLOps.
The predicted salary is between 70000 - 90000 £ per year.
We are seeking a Senior Data Scientist to join our greenfield AI team in London. In this role, you won’t just build models in isolation; you will own the entire lifecycle—from training and fine-tuning models to deploying them into production‑grade systems that power our global enterprise planning platform. This is a unique opportunity to bridge the gap between traditional predictive mathematics (such as high‑scale time‑series forecasting) and next‑generation Generative/Agentic AI. You will work across the full stack of our AI applications to build features that businesses rely on in real‑time.
- Advanced Modeling: Design, train, and implement advanced Machine Learning (ML) and Deep Learning (DL) models to solve complex business planning and forecasting problems.
- Predictive & Timeseries Forecasting: Develop robust, scalable time‑series models to enhance our platform’s predictive planning and scenario‑modeling capabilities.
- GenAI & LLM Integration: Implement and optimise Generative AI features, focusing on fine‑tuning open‑source LLMs (using LoRA, QLoRA, etc.) and building RAG pipelines.
- End-to-End Deployment (MLOps): Partner with our AI Engineers to transition your models from prototype into scalable, monitored, and reliable production microservices.
- Technical Mentorship: Actively contribute to code reviews, share technical best practices, and help mentor other data scientists and engineers on the team.
- Hands-on GenAI experience: Practical experience working with LLM APIs, prompt engineering, and fine‑tuning open‑source models.
- MLOps Exposure: Experience with tools and frameworks for training, deploying, and monitoring models in production.
- Production-grade Python: High proficiency in Python and modern software practices (TDD, clean code, code review, CI/CD).
- Strong predictive modeling foundation: Deep expertise in traditional ML algorithms and time‑series forecasting.
Senior Data Scientist employer: Anaplan
Anaplan in Manchester is an exceptional employer that prioritises diversity, equity, and inclusion, fostering a collaborative work culture where every voice is valued. Employees benefit from continuous growth opportunities through professional development and access to cutting-edge BI tools, making it an ideal environment for those looking to make a meaningful impact in the field of data analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Anaplan!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Scientist at Anaplan.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Anaplan.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Scientist at Anaplan, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Anaplan, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Anaplan. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Anaplan
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Anaplan!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
