At a Glance
- Tasks: Join our team to build AI data science solutions and collaborate with business stakeholders.
- Company: causaLens is revolutionizing AI data science, empowering teams to create custom data science agents.
- Benefits: Enjoy 25 days paid holiday, share options, learning budgets, and a great work-life balance.
- Why this job: Be part of a top-tier team, shaping the future of decision-making for leading enterprises.
- Qualifications: 2+ years of data science experience with Python; strong academic background in a quantitative field.
- Other info: Transparent interview process with opportunities for remote work and team outings.
The predicted salary is between 43200 - 72000 £ per year.
Get AI-powered advice on this job and more exclusive features. Direct message the job poster from causaLens. causaLens is pioneering the world’s first platform for building AI data scientists – empowering everyone to create and deploy their own data science agents in days. Our platform enables teams to collaborate in a multi-agent environment, ensuring human oversight across the entire workflow and making AI-powered data science trustworthy and accessible to everyone – from analysts to business leaders. We power industry leaders, including Cisco, Johnson & Johnson, Canon, and McCann Worldgroup, to accelerate and scale their data science capability. Join us to build the World’s First Platform for AI Data Scientists. What we are looking for We are looking for a Senior Data Scientist based in London to join our mission to create AI Data Scientists to radically advance decision-making for leading enterprises. You will join a team of 9 Data Scientists. We hire the top 1% of Data Science talent to create an intellectually stimulating environment where you can thrive and learn. You will be helping leading enterprises build their custom data science agents and help our users get the maximum out of the platform. What you will do As a Senior Data Scientist at causaLens, you will play a pivotal role in advancing our decision-making technology. This position demands a strong foundation in data science, particularly but not limited to time series, and using Python as the primary programming language. Some of your responsibilities will include: Using our Agentic AI framework to build data science solutions and models, using our platform on client-supplied data sets and use cases. Collaborating directly with business stakeholders to integrate domain knowledge into the modelling process, demonstrating how insights can enhance decision workflows. Crafting long-term visions and plans, in collaboration with clients and causaLens stakeholders, to successfully deploy agentic workflows into customers\’ strategies. Work closely with the product and engineering teams to shape the development of our platform. Communicate technical topics to non-technical audiences. Requirements At least 2 years of commercial data science experience using Python. Please note that this and the following bullet imply a significant breadth and depth of technical skills we will be testing for during the interview process – e.g., Statistics; other programming/scripting languages; solid understanding and experience with Cloud technologies; OOP, TDD, GitHub/Actions/Flow, and MLOps best practices; classical ML algorithms; at least some NLP, etc. Strong academic record in a quantitative field (MEng, MSci, EngD or PhD). Excellent and proven communication and teamwork skills. Previous experience in high-growth technology companies or technical consultancy is a plus. Previous experience in sales, pre-sales, and/or other technical evangelism is a plus. Experience with consulting and/or customer-facing roles, especially in the supply chain, demand forecasting, retail/cpg, manufacturing, marketing, financial services, or the public sector is a plus. Experience with LLM and RAG, GenAI, and agentic workflows is a plus. We care about our people’s lives, both inside and outside of causaLens. Beyond the core benefits like competitive remuneration, and a good work-life balance, we offer the following: 25 days of paid holiday, plus bank holidays. Buy/sell holiday options (up to 5 days). Share options. Happy hours and team outings. Cycle to work scheme. Friendly tech purchases. Benefits to choose from include Health/Dental Insurance. Special Discounts. Learning and development budget. Office snacks and drinks. Logistics Our interview process consists of a few screening interviews and a \”Day 0\” which is spent with the team (in-office). We will always be as transparent as possible so please don’t hesitate to reach out if you have any questions. If you require accommodations during the application process or in your role at causaLens, please contact us at talent@causalens.com Seniority level Mid-Senior level Employment type Full-time Job function Consulting, Engineering, and Other Industries Software Development #J-18808-Ljbffr
Applied Data Scientist employer: causaLens
Contact Detail:
causaLens Recruiting Team
talent@causalens.com
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Data Scientist
✨Tip Number 1
Familiarize yourself with causaLens' Agentic AI framework. Understanding how to leverage this platform will not only help you in the interview but also demonstrate your proactive approach and genuine interest in their technology.
✨Tip Number 2
Brush up on your Python skills, especially in the context of data science. Be prepared to discuss specific projects where you've used Python to solve complex problems, as this will be a key focus during the interview process.
✨Tip Number 3
Highlight any experience you have in consulting or customer-facing roles. Since collaboration with business stakeholders is crucial, showcasing your ability to communicate technical concepts to non-technical audiences will set you apart.
✨Tip Number 4
Research the industries that causaLens serves, such as retail, manufacturing, and financial services. Being able to discuss how your skills can specifically benefit these sectors will show that you're not just a fit for the role, but also for the company's mission.
We think you need these skills to ace Applied Data Scientist
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Senior Data Scientist position at causaLens. Familiarize yourself with their AI data science platform and how it integrates into business decision-making.
Tailor Your CV: Customize your CV to highlight relevant experience in data science, particularly with Python and time series analysis. Emphasize any previous work in high-growth technology companies or customer-facing roles that align with the job description.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your understanding of causaLens's mission. Mention specific projects or experiences that demonstrate your ability to collaborate with stakeholders and communicate technical concepts effectively.
Prepare for Technical Assessments: Since the interview process will test your technical skills, review key concepts in statistics, machine learning algorithms, and cloud technologies. Be ready to discuss your experience with MLOps best practices and any relevant programming languages beyond Python.
How to prepare for a job interview at causaLens
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and other programming languages. Highlight specific projects where you've applied statistical methods, machine learning algorithms, or cloud technologies. This will demonstrate your technical proficiency and readiness for the role.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Use examples from your past experiences to illustrate how you've successfully communicated insights to enhance decision-making.
✨Demonstrate Collaboration Experience
CausaLens values teamwork, so be ready to share examples of how you've collaborated with cross-functional teams. Discuss any experiences where you integrated domain knowledge into data science projects, showcasing your ability to work effectively with business stakeholders.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills and ability to apply your knowledge in real-world situations. Think about how you would approach building a data science solution using the Agentic AI framework and be ready to discuss your thought process.