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For Companies At a Glance
- Tasks: Develop cutting-edge NLP models and implement end-to-end ML solutions.
- Company: Join a leading financial services firm in London with a forward-thinking culture.
- Benefits: Enjoy competitive pay, great benefits, and the chance to work remotely.
- Why this job: Make a huge impact by driving innovation and solving real-world challenges in AI/ML.
- Qualifications: 4+ years in NLP, machine learning, and Python; deep learning expertise required.
- Other info: Bonus points for experience in financial data and Elasticsearch.
The predicted salary is between 48000 - 84000 £ per year.
Data Scientist / Machine Learning Engineer – NLP
Our leading financial services client based in London is seeking a first Data Scientist / NLP ML Engineer hire to join their crossfunctional engineering team to help them build out a number of impactful areas related to ML. Initially the requirement is building out from a POC that they have prototyped around document intelligence, and later to expand the nascent Data Science / ML function to explore uses for LLMs/chatbots, summarisation and others. You can have huge impact and really bring your experience to bear in this role at a forward-thinking organisation with great talent and culture. They pay extremely well and offer great benefits too.
What you'll do:
- Build Intelligent Systems: Develop state-of-the-art NLP models to extract crucial information from structured and unstructured text, and classify documents with precision, saving the firm huge time and effort.
- End to End ML: Implement end-to-end solutions, from data annotation to model deployment, ensuring systems are efficient, scalable, and accurate.
- Collaborate: Work alongside talented Strats, Engineers, Traders, and Operations experts to drive innovation and solve real-world challenges.
- Drive Business Impact: Identify opportunities to leverage AI/ML to streamline processes, improve decision-making, and unlock new growth avenues.
What you'll need:
- 4+ minimum years of hands-on experience in NLP, machine learning, and Python. This role suits someone who has seen DS/ML implemented in various places.
- Proficiency in deep learning / machine learning concepts & frameworks like TensorFlow, PyTorch, transformers, and others.
- Deep knowledge of AWS services, especially SageMaker.
- A drive to explore new techniques and push boundaries.
- The ability to articulate complex ideas to both technical and non-technical audiences and evangelise for data science / machine learning.
Bonus points for:
- Experience with information retrieval, search engine optimization and searchable databases i.e. Elasticsearch
- A knack for embedding generation and similarity search.
- Understanding of financial data and regulations.
- Textract experience a plus
Vertex Search are operating as a recruitment agency on this assignment.
Data Scientist / Engineer employer: Vertex Search
Contact Detail:
Vertex Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist / Engineer
✨Tip Number 1
Make sure to showcase your hands-on experience with NLP and machine learning in your conversations. Highlight specific projects where you've implemented these technologies, especially if they relate to document intelligence or similar areas.
✨Tip Number 2
Familiarize yourself with the latest trends in AI/ML, particularly in financial services. Being able to discuss recent advancements or case studies can demonstrate your passion and knowledge during interviews.
✨Tip Number 3
Prepare to discuss how you've collaborated with cross-functional teams in the past. This role emphasizes teamwork, so sharing examples of successful collaborations will show that you're a great fit for their culture.
✨Tip Number 4
If you have experience with AWS services, especially SageMaker, be ready to talk about it. Understanding cloud-based solutions is crucial for this position, and demonstrating your expertise can set you apart from other candidates.
We think you need these skills to ace Data Scientist / Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in NLP, machine learning, and Python. Include specific projects where you've developed NLP models or implemented end-to-end ML solutions.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with their needs, particularly in building intelligent systems and driving business impact through AI/ML.
Showcase Relevant Projects: Include examples of relevant projects in your application that demonstrate your proficiency with deep learning frameworks like TensorFlow and PyTorch, as well as your experience with AWS services, especially SageMaker.
Prepare for Technical Questions: Be ready to discuss your technical skills and experiences in detail. Prepare to articulate complex ideas clearly, as you may need to explain your work to both technical and non-technical audiences during interviews.
How to prepare for a job interview at Vertex Search
✨Showcase Your NLP Expertise
Be prepared to discuss your hands-on experience with NLP models. Highlight specific projects where you've developed or implemented state-of-the-art models, and be ready to explain the impact they had on the organization.
✨Demonstrate End-to-End ML Knowledge
Since the role involves implementing end-to-end solutions, make sure you can articulate your experience in the entire ML pipeline—from data annotation to model deployment. Discuss any challenges you faced and how you overcame them.
✨Collaborative Mindset
This position requires collaboration with various teams. Prepare examples of how you've successfully worked with cross-functional teams in the past, particularly with engineers and business stakeholders, to drive innovation.
✨Communicate Complex Ideas Simply
You’ll need to explain complex data science concepts to non-technical audiences. Practice simplifying your explanations and focus on how your work can drive business impact, making it relatable to different stakeholders.
