Data Scientist - AI/ML - Engineer - Manager

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

Join PwC US - Acceleration Center as a Manager of GenAI Data Science to lead innovative projects and drive significant advancements in GenAI solutions. We offer a competitive compensation package, a collaborative work environment, and ample opportunities for professional growth and impact. 

Years of Experience: Candidates with 8+ years of hands on experience

Responsibilities: 

• Lead and mentor a team of data scientists in understanding business requirements and applying GenAI technologies to solve complex problems. 

• Oversee the development, implementation, and optimization of machine learning models and algorithms for various GenAI projects. 

• Direct the data preparation process, including data cleaning, preprocessing, and feature engineering, to ensure data quality and readiness for analysis. 

• Collaborate with data engineers and software developers to streamline data processing and integration into machine learning pipelines. 

• Evaluate model performance rigorously using advanced metrics and testing methodologies to ensure robustness and effectiveness. 

• Spearhead the deployment of production-ready machine learning applications, ensuring scalability and reliability. 

• Apply expert programming skills in Python, R, or Scala to develop high-quality software components for data analysis and machine learning. 

• Utilize Kubernetes for efficient container orchestration and deployment of machine learning applications. 

• Design and implement innovative data-driven solutions such as chatbots using the latest GenAI technologies. 

• Communicate complex data insights and recommendations to senior stakeholders through compelling visualizations, reports, and presentations. 

• Lead the adoption of cutting-edge GenAI technologies and methodologies to continuously improve data science practices. 

• Champion knowledge sharing and skill development within the team to foster an environment of continuous learning and innovation. 

Requirements: 

• 8-10 years of relevant experience in data science, with significant expertise in GenAI projects. 

• Advanced programming skills in Python, R, or Scala, and proficiency in machine learning libraries like TensorFlow, PyTorch, or scikit-learn. 

• Extensive experience in data preprocessing, feature engineering, and statistical analysis. 

• Strong knowledge of cloud computing platforms such as AWS, Azure, or Google Cloud, and data visualization techniques. 

• Demonstrated leadership in managing data science teams and projects. 

• Exceptional problem-solving, analytical, and project management skills. 

• Excellent communication and interpersonal skills, with the ability to lead and collaborate effectively in a dynamic environment. 

Preferred Qualifications: 

• Experience with object-oriented programming languages such as Java, C++, or C#. 

• Proven track record of developing and deploying machine learning applications in production environments. 

• Understanding of data privacy and compliance regulations in a corporate setting. 

• Relevant advanced certifications in data science or GenAI technologies. 

Nice to Have Skills: 

• Experience with specific tools such as Azure AI Search, Azure Document Intelligence, Azure OpenAI, AWS Textract, AWS Open Search, and AWS Bedrock. 

• Familiarity with LLM backed agent frameworks like Autogen, Langchain, Semantic Kernel, and experience in chatbot development. 

Professional and Educational Background:

• Any graduate /BE / B.Tech / MCA / M.Sc / M.E / M.Tech /Master’s Degree /MBA 

The Opportunity

When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills.

As part of the Data and Analytics team you will design and deploy predictive models that turn complex data into actionable insights. As a Manager you will lead teams in delivering scalable analytics solutions while mentoring junior staff and maintaining project success. This is an exciting opportunity to join PwC US - Acceleration Center, where your skills in data science and machine learning will contribute to innovative AI solutions across various industries.

Responsibilities

- Design and implement predictive models to derive actionable insights

- Lead teams in developing scalable analytics solutions

- Mentor junior staff to build their capabilities in data science

- Secure successful project delivery through effectual management

- Collaborate with stakeholders to understand business needs and objectives

- Analyze complex data sets to inform strategic decisions

- Promote a culture of innovation and excellence within the team

- Uphold rigorous standards of quality and integrity in deliverables

What You Must Have

- Bachelor's Degree

- 7 years of experience

- Oral and written proficiency in English required

What Sets You Apart

- Master's Degree in Data Science, Computer Science, Statistics, Mathematics, Engineering

- Relevant certifications in Data Science, Cloud, or Machine Learning technologies

- Excelling in programming with Python and R

- Demonstrating experience in building and validating predictive models

- Utilizing cloud platforms for model training and deployment

- Applying statistical techniques for model performance validation

- Familiarity with containerization and orchestration tools

- Leading and mentoring teams of 5–10 members

- Experience in consulting engagements with client stakeholders

Travel Requirements

0%

Job Posting End Date