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For Companies At a Glance
- Tasks: Lead data extraction and analysis while developing predictive models in a dynamic environment.
- Company: Join a globally renowned bank known for innovation and excellence in financial services.
- Benefits: Enjoy flexible working options and access to cutting-edge technologies.
- Why this job: Be part of a collaborative culture that values tech-driven solutions and impactful projects.
- Qualifications: Experience in Python, Machine Learning, and financial services is essential.
- Other info: This role combines leadership with hands-on development, perfect for tech enthusiasts.
The predicted salary is between 48000 - 72000 £ per year.
Your new company
Working for a globally renowned bank.
Your new role
You will be working as a Technical Lead (60% Lead, 40% hands-on development). You will be responsible for data extraction, development, and analysis from structured/unstructured sources. Developing systems, cleaning results to build predictive/prescriptive models and implement them in a production environment by uniting with technology as well as business partners.
What you'll need to succeed
- Great experience as a Developer/Data Scientist with experience in financial services.
- Vast experience with programming in Python.
- Strong experience with Machine Learning/ML libraries.
- Numpy and Panda experience would be desirable.
- Proficiency in Spark/PySpark, TensorFlow, or other analytical/model-building programming languages.
What you'll get in return
- Flexible working options available.
- Access to market-leading technologies.
What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
Lead Data Lead (ML, Python) employer: Hays
Contact Detail:
Hays Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Lead (ML, Python)
✨Tip Number 1
Make sure to showcase your leadership skills during the interview. Since this role is 60% lead, be prepared to discuss your experience in managing teams and projects, and how you've successfully guided others in technical environments.
✨Tip Number 2
Brush up on your knowledge of financial services. Understanding the specific challenges and opportunities within the banking sector can set you apart from other candidates and demonstrate your commitment to the industry.
✨Tip Number 3
Prepare to discuss your hands-on experience with Python and ML libraries. Be ready to provide examples of projects where you've used Numpy, Pandas, or TensorFlow, and how these tools contributed to successful outcomes.
✨Tip Number 4
Familiarise yourself with Spark/PySpark if you haven't already. Being able to speak confidently about your experience with these technologies will show that you're well-equipped for the data extraction and analysis tasks outlined in the job description.
We think you need these skills to ace Lead Data Lead (ML, Python)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Python, Machine Learning, and any relevant financial services background. Use specific examples to demonstrate your skills in data extraction and model development.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your leadership experience. Mention how your technical skills align with the company's needs and how you can contribute to their projects.
Highlight Relevant Projects: Include details of specific projects where you've used Numpy, Pandas, Spark, or TensorFlow. Explain your role in these projects and the impact they had on the business or technology outcomes.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors. A polished application reflects your attention to detail, which is crucial for a Technical Lead role.
How to prepare for a job interview at Hays
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and Machine Learning in detail. Highlight specific projects where you've used libraries like Numpy, Pandas, or TensorFlow, and be ready to explain your thought process and the outcomes.
✨Demonstrate Leadership Experience
Since this role involves a significant leadership component, share examples of how you've led teams or projects in the past. Discuss your approach to mentoring others and how you ensure successful collaboration between technical and business partners.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges during the interview. Brush up on your problem-solving skills and be ready to tackle questions that require you to think critically about data extraction and model implementation.
✨Understand the Financial Services Sector
Familiarise yourself with the current trends and challenges in the financial services industry. Being able to discuss how your skills can address these issues will demonstrate your commitment and understanding of the sector.
