At a Glance
- Tasks: Lead data science projects to solve complex business problems using AI and machine learning.
- Company: Join a global tech transformation leader with 30 years of experience and over 1,000 clients.
- Benefits: Enjoy flexible working options, a collaborative culture, and opportunities for professional growth.
- Why this job: Make an impact by tackling real-world challenges for Fortune 500 companies while innovating with cutting-edge technology.
- Qualifications: Bachelor's in a quantitative field; proficiency in Python, R, SQL; strong communication skills required.
- Other info: We celebrate diversity and encourage applications from all backgrounds.
The predicted salary is between 48000 - 72000 £ per year.
We are tech transformation specialists, uniting human expertise with AI to create scalable tech solutions. With over 6,500 CI&Ters around the world, we’ve built partnerships with more than 1,000 clients during our 30 years of history. Artificial Intelligence is our reality.
General Description: We are looking for scientists who are passionate about data and are eager to tackle big challenges using Data Science and Machine Learning. The main focus of this role is to solve non-trivial business problems in Fortune 500 companies. This person will mostly work with a mix of structured and unstructured data, using scientific methods and state-of-the-art techniques and tools to help our customers achieve their business objectives.
Responsibilities:
- Understand complex business problems and translate them into structured data problems.
- Capture and explore complex data sets (structured and unstructured data).
- Prototype models of different complexity (business analysis, statistical models, machine learning) using modern data science tools (Notebooks, Clouds).
- Design and implementation of machine learning models, metrics, and application of feature engineering techniques applied to customer problems.
- Support pre-sales in business opportunities and the engineering teams in the implementation of production-ready solutions involving machine learning.
- Evaluate hypotheses and the impact of machine learning algorithms on key business metrics, including simulations and offline/online experimentation (via A/B tests).
- Research and understand user behavior patterns, such as user engagement and segmentation, using machine learning models to help test hypotheses.
- Communicate findings effectively to an audience of engineers and executives.
Required Qualifications:
- Bachelor’s Degree in Computer Science/Engineering, Applied Math, Statistics, Physics or other related quantitative areas.
- Advanced oral and written communication skills in English.
- Ability to understand mathematical models and algorithms in research papers and implement them into running software for Proof-of-Concepts and projects.
- Ability to explore big data without a specific problem defined, in order to come up with the right questions and provide interesting findings.
- Ability to provide visibility of the progress of tasks to the team by means of small deliverables.
- Proficient in computer languages like Python or R, and SQL, making use of the best frameworks for machine learning pipelines, data visualization, manipulation and transforming, models training and evaluation, and models deployment.
- Experience with common feature engineering techniques and machine learning algorithms for Supervised and Unsupervised Learning.
- Experience with Natural Language Processing (NLP and NLU).
- Experience using Generative AI systems (e.g. ChatGPT) and best practices (e.g. Prompt Engineering).
- Understanding the key concepts on how to apply Generative AI in building RAG solutions (embeddings, dense search).
- Business sense and consulting behavior to identify and breakdown problems, define and evaluate hypotheses.
- Think critically and act in a detail-oriented fashion while keeping the 'big picture' in mind.
- Ability to provide creative and innovative approaches to problem solving.
- Ability to work independently and within a collaborative team environment.
Desired Qualifications:
- Masters or PhD in Machine Learning / Data Mining / Statistics.
- Experience in building advanced Information Retrieval or Question Answering systems using NLP and Generative AI techniques (e.g. RAG and GraphRAG).
- Experience with construction and integration of Knowledge Graphs.
Collaboration is our superpower, diversity unites us, and excellence is our standard. We value diverse identities and life experiences, fostering a diverse, inclusive, and safe work environment. We encourage applications from diverse and underrepresented groups to our job positions.
[20702] Lead Data Scientist - UK 12 Month FTC employer: Ciandt
Contact Detail:
Ciandt Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land [20702] Lead Data Scientist - UK 12 Month FTC
✨Tip Number 1
Familiarise yourself with the latest trends in Data Science and Machine Learning, especially those relevant to Fortune 500 companies. This will not only help you understand the challenges they face but also allow you to speak confidently about how your skills can address these issues during interviews.
✨Tip Number 2
Engage with the Data Science community by attending meetups, webinars, or conferences. Networking with professionals in the field can provide insights into what companies like us are looking for and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your experience with both structured and unstructured data. Be ready to share specific examples of how you've tackled complex data problems and the impact your solutions had on previous projects.
✨Tip Number 4
Brush up on your communication skills, as you'll need to convey complex findings to both technical and non-technical audiences. Practising how to present your work clearly and effectively can set you apart from other candidates.
We think you need these skills to ace [20702] Lead Data Scientist - UK 12 Month FTC
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, machine learning, and any specific tools mentioned in the job description, such as Python, R, and SQL. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your ability to solve complex business problems. Mention specific projects or experiences that demonstrate your skills in handling structured and unstructured data.
Showcase Your Communication Skills: Since advanced communication skills are required, provide examples in your application of how you've effectively communicated complex findings to both technical and non-technical audiences. This could be through presentations, reports, or collaborative projects.
Highlight Relevant Qualifications: Clearly state your educational background and any advanced degrees you hold, especially if they relate to machine learning or data science. If you have experience with Generative AI or NLP, make sure to include that as well.
How to prepare for a job interview at Ciandt
✨Showcase Your Passion for Data
Make sure to express your enthusiasm for data science and machine learning during the interview. Share specific examples of projects you've worked on that demonstrate your passion and how you tackled complex data challenges.
✨Prepare for Technical Questions
Expect to be asked about your proficiency in programming languages like Python or R, as well as SQL. Brush up on common machine learning algorithms and feature engineering techniques, and be ready to discuss how you've applied them in real-world scenarios.
✨Communicate Clearly
Since you'll need to communicate findings to both engineers and executives, practice explaining complex concepts in simple terms. Use clear examples to illustrate your points and ensure that your communication skills shine through.
✨Demonstrate Problem-Solving Skills
Be prepared to discuss how you approach problem-solving. Think of a time when you had to explore big data without a defined problem and how you formulated the right questions to derive valuable insights. This will showcase your critical thinking and creativity.