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- Tasks: Lead AI/ML projects, collaborating with teams to solve real business challenges.
- Company: Join a leading Banking and Financial Services organisation making waves in the industry.
- Benefits: Enjoy flexible working options and a range of corporate perks.
- Why this job: Be at the forefront of AI advancements while making a significant impact in finance.
- Qualifications: Bring your expertise in machine learning, Python, and big data tools.
- Other info: Stay updated with the latest trends in Data Science and share insights with your team.
The predicted salary is between 48000 - 84000 £ per year.
Do you want to work for one of the biggest Banking and Financial Services organisations? If so, you will be:
- Partnering with product owners and business stakeholders to identify challenges, define use cases, and convert business requirements into AI/ML solutions.
- Creating, evaluating, and refining AI models to ensure they meet business objectives and comply with regulatory standards.
- Collaborating closely with MLOps engineers and the broader Tech and Data teams to implement production-ready solutions.
- Staying up-to-date with industry trends, especially in Data Science, NLP, and GenAI advancements, and sharing insights within the team.
You will require:
- Extensive experience in machine learning, deep learning, and statistical analysis.
- Proficient in Python, with expertise in ML and NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers, and PyTorch.
- Skilled in using big data tools such as Hadoop, Spark, and Hive.
- Knowledgeable in CI/CD and MLOps frameworks for developing end-to-end ML pipelines.
If this sounds like you, apply now!
Associate Director of Data Science employer: Hays
Contact Detail:
Hays Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Associate Director of Data Science
✨Tip Number 1
Network with professionals in the banking and financial services sector. Attend industry conferences, webinars, or meetups to connect with potential colleagues and learn about the latest trends in data science relevant to this field.
✨Tip Number 2
Showcase your experience with AI/ML solutions by discussing specific projects you've worked on. Be prepared to explain how you identified challenges, defined use cases, and implemented solutions that met business objectives.
✨Tip Number 3
Stay updated on the latest advancements in NLP and GenAI. Follow relevant blogs, podcasts, and research papers to ensure you can discuss current trends and innovations during interviews.
✨Tip Number 4
Familiarise yourself with the tools and frameworks mentioned in the job description, such as Scikit-learn, TensorFlow, and MLOps practices. Consider working on personal projects or contributing to open-source initiatives to demonstrate your proficiency.
We think you need these skills to ace Associate Director of Data Science
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your extensive experience in machine learning, deep learning, and statistical analysis. Include specific projects or achievements that demonstrate your proficiency in Python and relevant libraries.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your skills align with the job requirements, particularly your experience with AI/ML solutions and collaboration with tech teams.
Showcase Relevant Projects: If you have worked on projects involving big data tools like Hadoop, Spark, or Hive, be sure to mention these. Provide examples of how you developed end-to-end ML pipelines and any regulatory compliance you adhered to.
Stay Current with Industry Trends: Demonstrate your knowledge of current trends in Data Science, NLP, and GenAI advancements. Mention any recent developments you've followed and how they could impact the role you're applying for.
How to prepare for a job interview at Hays
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning, deep learning, and statistical analysis. Highlight specific projects where you've used Python and relevant libraries like Scikit-learn or TensorFlow, as this will demonstrate your technical proficiency.
✨Understand the Business Context
Familiarise yourself with the banking and financial services sector. Be ready to explain how your AI/ML solutions can address specific challenges faced by the industry, showing that you can translate business requirements into actionable data science strategies.
✨Collaborate Effectively
Emphasise your ability to work with cross-functional teams, especially MLOps engineers and tech teams. Prepare examples of past collaborations that led to successful project outcomes, as teamwork is crucial for implementing production-ready solutions.
✨Stay Current with Industry Trends
Demonstrate your knowledge of the latest advancements in Data Science, NLP, and GenAI. Share insights or recent developments that excite you, as this shows your passion for the field and your commitment to continuous learning.
