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- Tasks: Analyse data and develop machine learning models to solve real client problems.
- Company: Galytix is an innovative AI firm transforming banking and insurance with specialised knowledge assistants.
- Benefits: Enjoy career progression, work with industry leaders, and gain valuable skills in a dynamic environment.
- Why this job: Join a mission-driven team redefining industry standards and making a real impact on financial professionals.
- Qualifications: University degree in relevant fields and 6+ years of experience in data science and machine learning.
- Other info: Experience leading teams is a plus; strong problem-solving skills are essential.
The predicted salary is between 48000 - 72000 £ per year.
Galytix (GX) is delivering on the promise of AI. GX has built specialised knowledge AI assistants for the banking and insurance industry. Our assistants are fed by sector-specific data and knowledge and easily adaptable through ontology layers to reflect institution-specific rules. GX AI assistants are designed for Individual Investors, Credit and Claims professionals. Our assistants are being used right now in global financial institutions. Proven, trusted, non-hallucinating, our assistants are empowering financial professionals and delivering 10x improvements by supporting them in their day-to-day tasks. Responsibilities: Contributing by processing, analyzing, and synthesizing information applied to a live client problem at scale. Developing machine learning models to extract insights from both structured and unstructured data in areas such as NLP and Computer Vision. The role requires skills in both prototyping and developing individual solutions but also implementation and integration in a production environment. Desired Skills: A university degree in Mathematics, Computer Science, Engineering, Physics or similar. 6+ years of relevant experience in several areas of Data Mining, Classical Machine Learning, Deep Learning, NLP and Computer Vision. Experience with Large Scale/ Big Data technology, such as Hadoop, Spark, Hive, Impala, PrestoDb. Hands-on capability developing ML models using open-source frameworks in Python and R and applying them on real client use cases. Proficient in one of the deep learning stacks such as PyTorch or Tensorflow. Working knowledge of parallelisation and async paradigms in Python, Spark, Dask, Apache Ray. An awareness and interest in economic, financial and general business concepts and terminology. Excellent written and verbal command of English. Strong problem-solving, analytical and quantitative skills. A professional attitude and service orientation with the ability to work with our international teams. Experience in leading a team is an advantage. Why You Do Not Want to Miss This Career Opportunity: We are a mission-driven firm that is revolutionising the Insurance and Banking industry. We are not aiming to incrementally push the current boundaries; we redefine them. Customer-centric organisation with innovation at the core of everything we do. Capitalize on an unparalleled career progression opportunity. Work closely with senior leaders who have individually served several CEOs in Fortune 100 companies globally. Develop highly valued skills and build connections in the industry by working with top-tier Insurance and Banking clients on their mission-critical problems and deploying solutions integrated into their day-to-day workflows and processes. #J-18808-Ljbffr
Contact Detail:
Galytix Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Sr. Data Scientist London, UK
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Hadoop, Spark, and TensorFlow. Having hands-on experience or projects that showcase your skills in these areas can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the banking and insurance sectors, especially those who work with AI and data science. Attend industry events or webinars to make connections and learn more about the challenges they face, which can help you tailor your approach during interviews.
✨Tip Number 3
Prepare to discuss real-world applications of your machine learning models. Be ready to share examples of how you've solved complex problems using NLP or computer vision, as this will demonstrate your ability to apply your skills in a practical setting.
✨Tip Number 4
Showcase your understanding of economic and financial concepts during your interactions with the company. This knowledge will not only highlight your interest in the industry but also your ability to communicate effectively with stakeholders in the banking and insurance sectors.
We think you need these skills to ace Sr. Data Scientist London, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in areas like NLP and Computer Vision. Emphasise your hands-on experience with machine learning models and any specific technologies mentioned in the job description.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and its application in the banking and insurance sectors. Mention specific projects or experiences that align with the responsibilities of the role, demonstrating how you can contribute to Galytix's mission.
Showcase Your Technical Skills: In your application, clearly outline your proficiency with tools and frameworks such as Python, R, PyTorch, and TensorFlow. Provide examples of how you've used these skills in real-world scenarios, especially in developing ML models.
Highlight Team Leadership Experience: If you have experience leading teams, make sure to include this in your application. Discuss how your leadership has contributed to project success and how it aligns with the collaborative environment at Galytix.
How to prepare for a job interview at Galytix Limited
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning models, especially in NLP and Computer Vision. Bring examples of projects you've worked on, particularly those that involved large-scale data technologies like Hadoop or Spark.
✨Demonstrate Problem-Solving Abilities
Expect to tackle a live client problem during the interview. Practice articulating your thought process clearly and logically, as this will showcase your analytical skills and ability to synthesise information effectively.
✨Understand the Industry Context
Familiarise yourself with current trends in the banking and insurance sectors. Being able to discuss how AI can impact these industries will demonstrate your interest and understanding of the role's relevance.
✨Communicate Effectively
Since excellent written and verbal communication is crucial, practice explaining complex technical concepts in simple terms. This will help you connect with interviewers who may not have a technical background.
