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- Tasks: Join a small team to develop data analytics tools and models.
- Company: An Investment Manager based in London, focused on financial services.
- Benefits: Collaborative environment with opportunities for growth and learning.
- Why this job: Work with cutting-edge AI models and make a real impact in finance.
- Qualifications: Expertise in SQL, Python, AWS/Azure, and experience with AI models required.
- Other info: Strong communication skills are essential for stakeholder engagement.
The predicted salary is between 48000 - 84000 £ per year.
Senior Data Scientist
My client is and Investment Manager based in London, looking for a senior data scientist to join a small team. The Ideal candidate will have a background working in Financial Services firms with an impeccable command of SQL, Python, AWS or Azure. Prior experience working with AI models in data analytics is highly preferable.
Specification
- Expertise in Big Data manipulation and analysis, including the use of tools like Hadoop, Hive, and Spark
- Hands-on experience applying diverse AI and machine learning models to solve business challenges
- Advanced programming skills in Python and SQL
- Strong communication and stakeholder management abilities
- Experience with Azure and AWS
Day to day
Day to day you will be supporting a small team, you will be working closely with the lead data scientist alongside another Senior Data Scientist. You will be using and developing data analytics tools and models to support the wider business. Given the team size you will also be frequently working with stakeholders outside of the team. So, the ability to readily explain technical subject matter non-technically will be highly beneficial.
If this role sounds of interest please get in touch and apply today.
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Senior Data Scientist employer: Venn Group
Contact Detail:
Venn Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Make sure to showcase your experience in financial services during the interview. Highlight specific projects where you applied data science techniques to solve business problems, as this will resonate well with the hiring team.
✨Tip Number 2
Prepare to discuss your hands-on experience with AI models and big data tools like Hadoop, Hive, and Spark. Be ready to provide examples of how you've used these technologies to drive insights and support decision-making.
✨Tip Number 3
Since communication is key in this role, practice explaining complex technical concepts in simple terms. This will help demonstrate your ability to engage with stakeholders who may not have a technical background.
✨Tip Number 4
Familiarize yourself with the latest trends in data analytics and machine learning, especially in the context of financial services. Being able to discuss current developments will show your passion for the field and your commitment to staying updated.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your background in Financial Services and any specific projects where you've utilized SQL, Python, or cloud services like AWS or Azure. Tailor your experience to align with the job requirements.
Showcase Technical Skills: Clearly outline your expertise in Big Data tools such as Hadoop, Hive, and Spark. Provide examples of how you've applied AI and machine learning models to solve business challenges in your previous roles.
Demonstrate Communication Skills: Since the role involves stakeholder management, include examples of how you've effectively communicated complex technical concepts to non-technical audiences. This will show that you can bridge the gap between technical and non-technical team members.
Tailor Your Application: Customize your CV and cover letter to reflect the specific requirements mentioned in the job description. Use keywords from the listing to ensure your application stands out to hiring managers.
How to prepare for a job interview at Venn Group
✨Showcase Your Technical Skills
Be prepared to discuss your expertise in SQL, Python, and cloud platforms like AWS or Azure. Bring examples of past projects where you successfully applied these skills, especially in financial services.
✨Demonstrate AI and Machine Learning Knowledge
Highlight your experience with AI models and data analytics. Be ready to explain how you've used machine learning to solve business challenges, and consider discussing specific models you've implemented.
✨Communicate Clearly with Non-Technical Stakeholders
Since you'll be working closely with stakeholders outside your team, practice explaining complex technical concepts in simple terms. This will show your ability to bridge the gap between technical and non-technical teams.
✨Prepare for Team Dynamics
Understand the importance of collaboration in a small team. Be ready to discuss how you can contribute to team success and support your colleagues, particularly the lead data scientist.
