At a Glance
- Tasks: Develop predictive ML models for Ad Score and Account Health.
- Company: Join twentysix, a forward-thinking tech company in New York.
- Benefits: Enjoy a hybrid work model, competitive salary, and professional development.
- Other info: Collaborative team culture with exciting growth opportunities.
- Why this job: Make an impact with cutting-edge machine learning in a fast-paced environment.
- Qualifications: Master's or Ph.D. in relevant field, strong Python programming skills.
The predicted salary is between 60000 - 80000 £ per year.
twentysix is looking for an exceptional Machine Learning Engineer in New York. This role involves developing predictive ML models focusing on Ad Score and Account Health. You will analyze data, collaborate with engineers, and ensure effective deployment of models.
The ideal candidate has a Master's or Ph.D., expertise in machine learning and programming skills in Python. A fast-paced hybrid work environment with professional development opportunities is offered.
Lead ML Engineer - Ad Score & Account Health (Hybrid) employer: twentysix
At twentysix, we pride ourselves on being an exceptional employer that fosters a dynamic and innovative work culture in the heart of New York. Our hybrid work environment not only promotes flexibility but also encourages collaboration and professional growth, offering employees the chance to develop their skills in cutting-edge machine learning technologies. With a commitment to employee development and a focus on impactful projects, twentysix is the perfect place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Lead ML Engineer - Ad Score & Account Health (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at twentysix. A friendly chat can sometimes lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those related to predictive models. This will give you an edge and demonstrate your expertise in Python and machine learning.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge. Be ready to discuss your past projects and how they relate to Ad Score and Account Health. We want to see your passion and problem-solving skills!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect with us directly.
We think you need these skills to ace Lead ML Engineer - Ad Score & Account Health (Hybrid)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in machine learning and programming skills, especially in Python. We want to see how your background aligns with the role of Lead ML Engineer, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your expertise can contribute to our goals at twentysix. Keep it engaging and personal – we love to see your passion!
Showcase Your Projects:If you've worked on any predictive ML models or similar projects, make sure to mention them in your application. We’re keen to see real-world examples of your work, so include links or descriptions that highlight your contributions.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at twentysix
✨Know Your ML Models Inside Out
Make sure you can discuss various machine learning models and their applications, especially those relevant to Ad Score and Account Health. Be prepared to explain your thought process behind model selection and how you've implemented them in past projects.
✨Show Off Your Python Skills
Since programming in Python is crucial for this role, brush up on your coding skills. Be ready to tackle coding challenges or explain your previous projects where you used Python for machine learning tasks. Practice writing clean, efficient code.
✨Data Analysis is Key
Demonstrate your ability to analyse data effectively. Prepare examples of how you've used data analysis to inform your machine learning models. Discuss any tools or libraries you’ve used, and be ready to talk about the insights you derived from your analyses.
✨Collaboration is Crucial
This role involves working closely with engineers, so highlight your teamwork skills. Share experiences where you collaborated on projects, how you communicated complex ideas, and how you ensured successful deployment of models in a team setting.
