At a Glance
- Tasks: Lead exciting projects in data science and AI, building advanced GenAI applications.
- Company: Join LexisNexis, a leader in innovative data solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Be part of a fast-paced team driving measurable business success.
- Why this job: Make a real impact with cutting-edge AI and ML technologies.
- Qualifications: Strong Python and AWS skills, plus a solid machine learning foundation.
The predicted salary is between 60000 - 80000 € per year.
LexisNexis is seeking a Senior Data Scientist II to lead impactful projects in data science and AI. The ideal candidate will design, build, and deploy advanced AI and ML solutions, collaborating across various business functions.
Responsibilities include:
- Building GenAI applications
- Developing ML models
- Managing the model lifecycle
The role demands strong Python and AWS skills, with a solid foundation in machine learning. This position offers an exciting opportunity to work in a fast-moving Data Science team focused on delivering measurable business impact.
Senior Data Scientist II: GenAI & End-to-End ML Lead employer: LexisNexis
At LexisNexis, we pride ourselves on being an exceptional employer that fosters innovation and collaboration within our dynamic Data Science team. Our commitment to employee growth is evident through continuous learning opportunities and a supportive work culture that values creativity and impact. Located in a vibrant environment, we offer competitive benefits and the chance to work on cutting-edge AI and ML projects that drive real business outcomes.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist II: GenAI & End-to-End ML Lead
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at LexisNexis. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've built any cool GenAI applications or ML models, make sure to have them ready to discuss. Real-world examples can really set you apart from the crowd.
✨Tip Number 3
Prepare for the technical interview! Brush up on your Python and AWS skills, and be ready to tackle some coding challenges. We all know that hands-on experience speaks volumes.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the team.
We think you need these skills to ace Senior Data Scientist II: GenAI & End-to-End ML Lead
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your Python and AWS expertise in your application. We want to see how you’ve used these skills in real projects, especially in building GenAI applications or ML models.
Tailor Your Application:Don’t just send a generic CV! Tailor your application to reflect the responsibilities mentioned in the job description. Show us how your experience aligns with leading impactful data science projects.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured information that makes it easy for us to see your qualifications and experiences at a glance.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity in our fast-moving Data Science team!
How to prepare for a job interview at LexisNexis
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and AWS, as these are crucial for the role. Brush up on your knowledge of machine learning concepts and be ready to discuss how you've applied them in past projects.
✨Showcase Your Project Experience
Prepare to talk about specific GenAI applications or ML models you've developed. Highlight the impact these projects had on previous teams or businesses, and be ready to explain your thought process and decision-making.
✨Collaborative Spirit is Key
Since the role involves working across various business functions, be prepared to discuss how you’ve collaborated with different teams in the past. Share examples that demonstrate your ability to communicate complex data science concepts to non-technical stakeholders.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company’s data strategy and future projects. This not only demonstrates your enthusiasm but also helps you gauge if the company aligns with your career goals.
