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- Tasks: Design and prototype innovative data science solutions using AI and NLP.
- Company: Curve is a cutting-edge consultancy transforming consumer data into actionable insights.
- Benefits: Enjoy a fast-paced start-up environment with opportunities for growth and learning.
- Why this job: Join a passionate team pushing the boundaries of AI and data science in a dynamic setting.
- Qualifications: Bachelor's degree in a relevant field and 3+ years of Python experience required.
- Other info: Exciting chance to shape the future of a growing London start-up.
The predicted salary is between 36000 - 60000 £ per year.
Curve is a next-gen insights, analytics and technology consultancy that leverages digital consumer data and advanced technology to help businesses unlock consumer opportunities. Digital consumer data is powerful; it’s big, it’s real, and it’s always updating. We use a combination of in-house technology and bespoke solutions, powered by AI, to transform data from sources such as Social, Reviews, Search, and broader marketing and sales data. These reveal fresh insights for our clients; helping them to build better products and brands, to deliver effective marketing to consumers.
Our software, machine learning and AI are key to how we deliver impact, centred on:
- Natural Language Processing, GPT & other LLMs: unearthing trends, themes and other patterns from large text-based data sets, and deploying state-of-the-art AI to automate and empower consumer facing businesses and their insights & analytics functions
- Marketing Data Science & Personalisation: using first party consumer data to understand each client’s consumer base, building personalisation and other machine learning models to better engage with and excite consumers
- Data Engineering & Data Architecture: data engineering across a variety of tools to integrate these leading technologies into optimised and efficient data models and ecosystems, feeding into best-in-class analytics dashboards, marketing activation and front-end platforms
- Software Engineering: full stack expertise to build, maintain and support internal and externally facing Software & Data as a Service solutions, in AWS, that accelerate delivery and unlock deeper insights for our clients
As a start-up, we can move faster than most companies and do things differently. We have experienced rapid growth so far and we’re looking for a AI Engineer to join our growing team.
ABOUT THE ROLE
You’ll play a crucial role in designing, prototyping and evaluating innovative data science solutions, powered by digital consumer data sources. Through your proactive research, and driven by your passion for data science, you’ll surface the latest AI and NLP innovations, connecting the dots with Curve’s use cases to propose novel solutions to our most challenging problems. You’ll work on a mix of small proof of concepts and larger projects, both of which push the boundaries of what we can do with digital data and technology; building innovative models on top of the latest open source tools, as well as making use of cutting edge AI APIs from OpenAI, Google, Microsoft and AWS.
You’ll regularly share your knowledge of the rapidly changing and exciting world of AI to ensure Curve benefits from your ongoing research. Additionally, you’ll work to shape the future of our fast-growing London start-up, driving and enhancing our data science capabilities and best practices as we continue to grow, playing a key part in maintaining our Technology Team’s competitive edge.
We are looking for a passionate and ambitious data scientist, enthusiastic about continuously learning through exploring and experimenting with trends in data science and NLP, with a keen interest in applying innovative approaches to digital consumer data sources for the benefit of Curve and our clients.
WHAT YOU’LL BE DOING
- Develop innovative data science models and prototypes in Python, from scratch
- Proactively research, experiment with, and share the latest trends in data science, AI and NLP
- Translate unstructured business problems into clear requirements
- Interrogate and data mine rich digital consumer data sources such as social posts, search engine data, product reviews, clickstream data and beyond
- Proactively and continuously identify and propose ways to improve the impact of our data solutions
- Explore new and novel ways to understand and enrich digital consumer data sources
- Work closely with an amazing cross-functional Curve team from specialists in data science & engineering to strategy, insights and analytics experts
WHAT WE’RE LOOKING FOR
- Bachelor’s degree or higher in an applicable field such as Computer Science, Statistics, Maths or similar Science or Engineering discipline
- Experience designing, developing, evaluating and optimising data science models and NLP solutions
- 3+ years’ experience with Python, with strong code design skills, and preferably OOP experience
- Passionate about AI and NLP, with demonstrable experience researching, experimenting with and communicating the benefits of new data science technologies and methods
- Some experience with defining hypotheses and running effective data science experiments
- SQL and some data warehousing knowledge
NICE TO HAVES OR EXCITED TO LEARN:
- Experience analysing data in a marketing or other consumer-centric context
- Experience developing data solutions in cloud environments such as Azure, AWS or GCP
- Experience utilising social listening tools and/or search/web analytics tools
Get to know Curve\’s journey and meet some of the minds fuelling our passion
#J-18808-Ljbffr
AI Engineer employer: Curveanalytics
Contact Detail:
Curveanalytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in AI and NLP. Follow industry leaders on social media, read relevant blogs, and participate in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Engage with the data science community by attending meetups or webinars focused on AI and machine learning. Networking with professionals in the field can provide valuable insights and potentially lead to referrals for job opportunities at Curve.
✨Tip Number 3
Showcase your skills through personal projects or contributions to open-source initiatives. Building a portfolio that highlights your experience with Python, data models, and NLP solutions will make you stand out as a candidate.
✨Tip Number 4
Prepare to discuss how you've tackled real-world data problems in previous roles. Be ready to share specific examples of how you've used data science to drive insights or improve processes, as this aligns closely with what Curve is looking for.
We think you need these skills to ace AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI, NLP, and data science. Focus on projects where you've developed models or worked with digital consumer data, as this aligns closely with Curve's needs.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and data science. Mention specific technologies or methodologies you’ve used that relate to the job description, such as Python, machine learning, or cloud environments.
Showcase Your Projects: If you have any personal or professional projects that demonstrate your skills in developing data science models or working with AI, include them in your application. This could be through a portfolio or links to GitHub repositories.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops you've attended related to AI, NLP, or data science. This shows your commitment to staying updated with the latest trends and technologies, which is crucial for a role at Curve.
How to prepare for a job interview at Curveanalytics
✨Showcase Your Passion for AI and NLP
Make sure to express your enthusiasm for artificial intelligence and natural language processing during the interview. Share specific examples of projects or research you've undertaken that demonstrate your passion and knowledge in these areas.
✨Prepare to Discuss Your Technical Skills
Be ready to talk about your experience with Python and any data science models you've developed. Highlight your coding skills, especially in object-oriented programming, and be prepared to discuss how you've optimised models in past roles.
✨Demonstrate Problem-Solving Abilities
Expect to encounter questions that assess your ability to translate unstructured business problems into clear requirements. Prepare examples of how you've approached complex problems in the past and the innovative solutions you proposed.
✨Research Curve and Its Technologies
Familiarise yourself with Curve's approach to leveraging digital consumer data and the technologies they use. Understanding their products and services will help you align your answers with their goals and show that you're genuinely interested in the company.
