Associate
PwC is hiring an Associate. Level rates it ; you can apply on PwC.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions visa sponsorship.
- The posting mentions PyTorch, TensorFlow and scikit-learn among its tools and skills.
- Level classes it as a junior role.
- PwC has 3,700+ other open roles on Level.
AI in this role
Line of Service
TaxIndustry/Sector
Not ApplicableSpecialism
OperationsManagement Level
AssociateJob Description & Summary
A career within Regulatory Risk and Compliance services, will provide you with the opportunity to help companies rethink their approach to risk and create a sustainable risk advantage. We’re a part of a unique client proposition, assisting our clients develop proper internal controls by leveraging analytics and technology solutions to underpin efficient execution of governance, to optimise their risk and compliance policies and processes, and improve business performance.Job Description & Summary
Why PWC
At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us.
A career within GenAI Data Scientist / Python Developer, will provide you with the opportunity to help our clients leverage Salesforce technology to enhance their customer experiences.
We are seeking a skilled and innovative GenAI Data Scientist/Python Developer to join our dynamic team. The ideal candidate will have deep expertise in developing, deploying, and optimizing AI models with a strong emphasis on Generative AI. You will work closely with cross-functional teams to create advanced data-driven solutions that address complex business challenges.
Key Responsibilities:
- Model Development and Deployment:
- Design, develop, and implement Generative AI models (such as GPT, GANs, VAEs) for various applications.
- Optimize and fine-tune AI models for performance, scalability, and accuracy.
- Deploy AI models into production environments using cloud platforms (AWS, GCP, Azure) and MLOps practices.
- Data Science and Analysis:
- Perform data preprocessing, feature engineering, and exploratory data analysis (EDA).
- Develop and validate predictive models using machine learning techniques.
- Utilize statistical methods and algorithms to analyze large datasets and extract meaningful insights.
- Python Development:
- Write clean, efficient, and scalable Python code for AI model development and deployment.
- Build and maintain data pipelines, APIs, and automation scripts.
- Integrate AI models with existing software systems and services.
- Collaboration and Communication:
- Work closely with data engineers, product managers, and stakeholders to understand business needs and translate them into technical requirements.
- Present findings, model performance, and insights to both technical and non-technical audiences.
- Contribute to research and development efforts, staying up-to-date with the latest advancements in AI and data science.
*Mandatory skill sets
- Technical Skills:
- Proficient in Python, with a strong understanding of libraries such as TensorFlow, PyTorch, scikit-learn, and pandas.
- Experience with Generative AI models (e.g., GPT, GANs) and natural language processing (NLP).
- Strong background in machine learning, deep learning, and statistical modeling.
- Familiarity with cloud computing platforms (AWS, GCP, Azure) and MLOps tools.
- Experience with version control (Git) and CI/CD pipelines.
- Soft Skills:
- Strong problem-solving skills and attention to detail.
- Ability to work independently as well as collaboratively in a team environment.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience in developing AI solutions for specific industries (e.g., Pharma, finance, retail).
- Publications or contributions to AI/ML communities or conferences.
- Familiarity with containerization and orchestration tools (Docker, Kubernetes)
*Preferred skill sets
- Soft Skills:
- Strong problem-solving skills and attention to detail.
- Ability to work independently as well as collaboratively in a team environment.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience in developing AI solutions for specific industries (e.g., Pharma, finance, retail).
- Publications or contributions to AI/ML communities or conferences.
Familiarity with containerization and orchestration tools (Docker, Kubernetes
*Year of experience required
- 3+ years of experience in data science, AI, or machine learning roles.
- Proven track record of deploying AI models in production environments.
- Experience in working with large datasets and big data technologies
*Educational Qualification
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor Degree, Master of Engineering, Master of Business Administration, Master Degree, Bachelor of EngineeringDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)
Required Skills
Git, Machine Learning Operations, Natural Language Processing (NLP), Python (Programming Language)Optional Skills
Desired Languages (If blank, desired languages not specified)
Travel Requirements
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date
How we rate this
Associate at PwC rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What are the limits of PyTorch that you've run into, and how did you work around them?
- What's a project where you used TensorFlow hands-on?
- Walk me through how you've used scikit-learn in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: ML Ops, NLP, PyTorch, TensorFlow, and scikit-learn. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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