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- Tasks: Coach and mentor teams on practical machine learning solutions and workflows.
- Company: Join a forward-thinking company that values innovation and collaboration.
- Benefits: Hybrid working model, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with a focus on building confidence and trust in ML.
- Why this job: Empower others to embrace ML and make a real impact in their work.
- Qualifications: Strong Python skills and hands-on ML experience required.
The predicted salary is between 60000 - 80000 ÂŁ per year.
The ML Enablement Lead focuses on building ML capability and confidence within the business. This role supports stakeholders who are new to machine learning and Databricks, helping them understand where ML adds value and how to use it effectively. The emphasis is on coaching, skills transfer, and change adoption, rather than complex or academic modelling.
Key responsibilities
- Work closely with business and technical stakeholders who are early in their ML journey
- Provide hands‑on coaching, mentoring, and guidance
- Support teams in building confidence with ML concepts and workflows
- Guide stakeholders through:
- Problem framing for ML
- Feature selection and model development
- Model evaluation and interpretation
- Adds real business value
- Is feasible within current skills and data
- Experiment tracking
- Version control
- Basic deployment considerations
Must‑have skills
- Strong Python skills within the ML ecosystem
- Hands‑on, applied ML experience
- Understanding of MLOps fundamentals
- Excellent communication, teaching, and coaching ability
- Strong stakeholder engagement skills
- Ability to simplify complex topics
- Good business understanding and pragmatic mindset
- Ability to self‑start and work proactively
- Patience, coaching mindset, and focus on stakeholder needs
Nice to have
- Databricks experience
- Deep learning experience
ML Enablement Lead/Senior Applied Data Scientist employer: Cognizant Technology Solutions
Contact Detail:
Cognizant Technology Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Enablement Lead/Senior Applied Data Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Prepare for those interviews by practising common questions and scenarios related to ML. We suggest doing mock interviews with friends or using online platforms to get comfortable talking about your skills and experiences.
✨Tip Number 3
Showcase your projects! Whether it's a GitHub repo or a personal blog, we recommend having a portfolio that highlights your hands-on experience with ML. This gives potential employers a taste of what you can do.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to navigate!
We think you need these skills to ace ML Enablement Lead/Senior Applied Data Scientist
Some tips for your application 🫡
Show Your Passion for ML: Let us see your enthusiasm for machine learning! In your application, share why you're excited about the role and how you can help others on their ML journey. A genuine passion can really make you stand out.
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your relevant experience and skills. We want to see how your background aligns with our focus on coaching and practical ML solutions, so don’t hold back!
Keep It Clear and Concise: When writing your application, aim for clarity. Use straightforward language and avoid jargon where possible. Remember, we value the ability to simplify complex topics, so show us you can do that right from the start!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Cognizant Technology Solutions
✨Know Your ML Basics
Make sure you brush up on the fundamental concepts of machine learning. Understand how to explain problem framing, feature selection, and model evaluation in simple terms. This will help you connect with stakeholders who are new to ML and demonstrate your ability to simplify complex topics.
✨Showcase Your Coaching Skills
Prepare to discuss your experience in coaching and mentoring others. Think of specific examples where you've helped someone understand ML concepts or workflows. Highlight your patience and ability to adapt your teaching style to meet different learning needs.
✨Be Ready for Practical Scenarios
Expect questions that focus on real-world applications of ML. Be prepared to share how you've guided teams towards practical solutions rather than perfect ones. Discuss any hands-on experience you have with MLOps practices like experiment tracking and version control.
✨Engage with Stakeholders
Demonstrate your strong stakeholder engagement skills by preparing questions that show your interest in their needs. Think about how you can build trust with non-expert users and support them in their ML journey. This will highlight your understanding of the business value of ML.