Level

PwCPosted 24mo ago

Associate

Associate at PwC scores 96 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Bengaluru MilleniajuniorFull time

AI in this role

pytorchtensorflowscikit-learn
ml-opsnlp

Line of Service

Tax

Industry/Sector

Not Applicable

Specialism

Operations

Management Level

Associate

Job 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 Engineering

Degrees/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

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Ml OpsNlpPyTorchTensorFlowscikit-learn

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. What NLP problem have you worked on, and how did you measure whether it actually worked?
  3. What are the limits of PyTorch that you've run into, and how did you work around them?
  4. What's a project where you used TensorFlow hands-on?
  5. 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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