Data Science Intern Cardiff

·
Internship
Location: Cardiff
·
Job offered by: ANNA Money
·
Category: IT & Technology
Main:

Salary: £35,000 per annum or more, depending on your qualifications. Location: Hybrid or fully remote, at least 5 days during onboarding and 1 day per week on-site at the London office near King's Cross or Cardiff. Duration: 3 months, and hopefully you will stay with us longer. Start date: Whenever you are ready. Visa: You must have the right to work in the UK during your internship; we don't support internship visas. About ANNA:

ANNA is a UK-based financial service designed for freelancers and small businesses. One of the

Top 25 UK Startups 2024 by Bloomberg.

We're growing quickly, both in active users and revenue, and are looking for talented interns to join us in developing key business administration and compliance areas. You can learn more about us

here (

https://anna.money/careers/all-about-anna/

). What you will be doing:

We will assign you one of the projects based on your interests and competencies. Samples of the projects that you might be working on:

Improving our AI chat-based tax assistant Tax Terrapin (try it yourself:

https://anna.money/free-tools/chatgpt-tax-terrapin/ ), ensuring it delivers exceptional, personalised, and proactive support to small business customers. Enhance fraud detection models and create transaction monitoring rules to identify fraudulent activities efficiently. Develop a digital profile of our customers - neural network embeddings we could use for many downstream tasks. Develop LLM-based multi-modal systems for interviewing our customers and performing other information requests. And what exactly you will be doing:

Design systems to provide context-aware, personalised responses based on business profiles, transactions, and documents. Build and implement efficient LLM applications using modern Python frameworks with providers like OpenAI, Anthropic, and Google. Work with data annotators to test new AI use cases and collect datasets based on user history logs. Deploy applications to real customers using Google Cloud, Kubernetes, and advanced CI/CD pipelines. Create LLM-based multi-modal systems. Key Features Of The Internship:

Dedicated mentor who will provide consistent guidance and ensure that the results of experiments reach clients. Weekly syncs with the Head of Data Science to discuss challenges, brainstorm solutions, and receive constructive feedback to ensure your success. Cross-functional team where developers and designers will assist you. We use the Agile framework and believe in hypothesis testing using a minimum valuable product. Salary, bank holidays, and other typical corporate perks. Expected Outcomes:

You will improve the lives of tens of thousands of ANNA's clients. The technical and practical experience gained will be highly valuable for your future career anywhere in AI, Data Science, and Machine Learning, especially in fintech. If you and we are satisfied with the results, we will make you a job offer that will wait until graduation. We will help you start building your personal brand by highlighting your work and achievements in a post on the company blog. I.e., Meet Our Intern Georgia Hirth ( https://anna.money/blog/interviews/meet-our-intern-georgia-hirth/ ). Skills And Experience

Minimum:

Proficiency in Python, SQL, and libraries for data manipulation and exploration like Pandas and NumPy. Experience in natural language processing (NLP), time-series data modelling or graph-based models. Basic understanding of statistical analysis: you should know how to differentiate good results from statistical noise. Desirable — the more of the below you have, the higher salary you will have:

Demonstrable experience in building software solutions to solve real-life challenges. Have a deep understanding of statistical machine learning and optimisation techniques. Experience with DevOps tools (Git, Github-actions, Docker, etc.). Experience with MLOps tools (DVC, MLflow, Seldon, KServe). Experience solving real-world tasks with prompt engineering, RAG, testing and evaluation techniques for LLMs. Experience with object-oriented Python, web-scraping, and cloud services. Experience working with financial data.

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