Data Science Lead: AI, NLP & MLOps Champion

Data Science Lead: AI, NLP & MLOps Champion

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Mphasis

At a Glance

  • Tasks: Lead innovative AI and Machine Learning projects that drive real business results.
  • Company: Mphasis, a forward-thinking tech company with a collaborative vibe.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Dynamic role with mentorship opportunities and cutting-edge technology.
  • Why this job: Join a team shaping the future of AI and make a significant impact.
  • Qualifications: 6+ years in Data Science, strong NLP skills, and proficiency in Python and TensorFlow.

The predicted salary is between 60000 - 80000 £ per year.

Mphasis is seeking a passionate Data Science Lead to spearhead the development of advanced AI and Machine Learning solutions that deliver measurable business impact. You will lead end-to-end data science initiatives, building scalable solutions and mentoring teams.

We’re looking for a candidate with 6+ years of hands-on experience in Data Science and Machine Learning, strong expertise in NLP, and proficiency in tools like Python, Scikit-Learn, and TensorFlow. This role offers the chance to work on cutting-edge projects within a collaborative environment.

Data Science Lead: AI, NLP & MLOps Champion employer: Mphasis

Mphasis is an excellent employer for those looking to make a significant impact in the field of Data Science. With a strong focus on innovation and collaboration, employees benefit from a dynamic work culture that encourages professional growth through mentorship and hands-on experience with advanced AI and Machine Learning technologies. Located in a vibrant tech hub, Mphasis offers unique opportunities to work on cutting-edge projects while being part of a supportive team dedicated to driving measurable business outcomes.

Mphasis

Contact Details:

Mphasis Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Science Lead: AI, NLP & MLOps Champion

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Mphasis!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Science Lead: AI, NLP & MLOps Champion at Mphasis.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Mphasis.

Apply Directly through Our Website

When you find a suitable opening like Data Science Lead: AI, NLP & MLOps Champion at Mphasis, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Science Lead: AI, NLP & MLOps Champion

Data Science
Machine Learning
Natural Language Processing (NLP)
Python
Scikit-Learn
TensorFlow
End-to-End Data Science Initiatives

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Mphasis, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Mphasis. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Mphasis

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Mphasis!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.