At a Glance
- Tasks: Join our team to develop cutting-edge AI and NLP solutions for real-world business challenges.
- Company: PwC is a leading professional services firm, innovating with AI across various industries.
- Benefits: Enjoy flexible working options, private medical cover, and six volunteering days annually.
- Why this job: Be at the forefront of AI technology, collaborating with diverse teams to drive innovation.
- Qualifications: 2+ years in data science, proficiency in Python, and experience with machine learning frameworks required.
- Other info: Opportunities available in Manchester, Leeds, Birmingham, and London.
The predicted salary is between 43200 - 72000 £ per year.
The AI and Emerging Technologies team identifies and develops AI solutions that solve hard problems for PwC and for its clients. Our team works at the frontier of AI and ML in professional services, across multiple industries including healthcare, financial services, and professional services. We are looking for people to contribute to the development of AI tools and solutions, and help the business build capabilities on cutting-edge AI and NLP techniques.
We're currently looking for a motivated, self-starter individual, comfortable with ambiguity, and willing to work in a cross-functional environment, with 2+ years of experience in data science, to join us across our Manchester, Leeds, Birmingham, and London offices.
What your days will look like:
- Solution Development: Contribute to designing, developing and scaling AI and NLP solutions addressing specific business problems or opportunities. This involves understanding business requirements, assessing feasibility, selecting appropriate techniques and technologies, and creating scalable and efficient solutions.
- AI Strategy: Contribute to the organisation's AI strategy by identifying opportunities for leveraging AI technologies to drive innovation, improve business processes, and enhance decision-making. This includes staying updated on AI trends and advancements, conducting market research, and providing recommendations on AI adoption and implementation.
- Model Development and Evaluation: Contribute to the development, deployment, and evaluation of AI models and to the deployment and evaluation of off the shelf AI models. This includes selecting appropriate algorithms, optimising model performance, conducting experiments and testing, and ensuring that the models meet the desired accuracy, reliability, and performance criteria.
- Collaboration and Stakeholder Management: Help the wider team collaborating with business stakeholders, technology teams, and other relevant groups to understand their needs, gather requirements, and align AI solutions with organisational goals.
Key Responsibilities:
- Prototyping, developing, and deploying machine learning applications into production.
- Contributing to our machine learning enabled, business-facing applications.
- Contributing effective, high quality code to our codebase.
- Model validation and model testing of production models.
- Presenting findings to senior internal and external stakeholders in written reports and presentations.
This role is for you if:
- Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow).
- Understanding of machine learning techniques.
- Experience with data manipulation libraries (e.g. Pandas, Spark, SQL).
- Problem solving skills.
- Git for version control.
- Cloud experience (we use Azure/GCP/AWS).
Skills we'd also like to hear about:
- Evidence of modelling experience applied to industry relevant use cases.
- Familiarity with working in an MLOps environment.
- Familiarity with simulation techniques.
- Familiarity with optimisation techniques.
What you'll receive from us:
No matter where you may be in your career or personal life, our benefits are designed to add value and support, recognising and rewarding you fairly for your contributions. We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.
Data Scientist employer: PricewaterhouseCoopers
Contact Detail:
PricewaterhouseCoopers Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in AI and machine learning. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews, showcasing your passion and knowledge about the field.
✨Tip Number 2
Network with professionals in the data science and AI community. Attend meetups, webinars, or conferences related to AI and ML. Building connections can lead to valuable insights and potential referrals for the position at StudySmarter.
✨Tip Number 3
Prepare to discuss specific projects you've worked on that demonstrate your skills in Python, machine learning frameworks, and data manipulation. Be ready to explain your thought process and the impact of your work, as this will highlight your problem-solving abilities.
✨Tip Number 4
Showcase your collaboration skills by preparing examples of how you've worked with cross-functional teams in the past. Highlighting your ability to communicate effectively with stakeholders will be crucial, as this role involves significant teamwork.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with AI and machine learning. Emphasise your skills in Python, model development, and any specific projects that align with the job description.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and emerging technologies. Discuss how your background and skills make you a perfect fit for the role, and mention specific examples of your work that demonstrate your problem-solving abilities.
Showcase Relevant Projects: Include a portfolio or a section in your CV that details projects you've worked on related to AI, NLP, or machine learning. Highlight your contributions, the technologies used, and the impact of these projects on business outcomes.
Prepare for Technical Questions: Anticipate technical questions related to machine learning frameworks, data manipulation, and model evaluation. Be ready to discuss your approach to problem-solving and how you stay updated on industry trends in AI.
How to prepare for a job interview at PricewaterhouseCoopers
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, machine learning frameworks like Sklearn, and deep learning tools such as Pytorch and Tensorflow. Highlight specific projects where you've applied these skills to solve real-world problems.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your problem-solving skills. Prepare examples of how you've tackled complex data challenges in the past, focusing on your thought process and the techniques you employed.
✨Understand the Business Context
Research PwC's AI and Emerging Technologies team and understand their focus areas. Be ready to discuss how your work can align with their goals and contribute to their AI strategy, showcasing your understanding of industry trends.
✨Prepare for Collaboration Questions
Since collaboration is key in this role, think of examples where you've worked effectively in cross-functional teams. Be ready to discuss how you gathered requirements from stakeholders and aligned your solutions with organisational objectives.