Data Science -Associate 2

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.

Driven by curiosity, you are a reliable, contributing member of a team. In our fast-paced environment, you are expected to adapt to working with a variety of clients and team members, each presenting varying challenges and scope. Every experience is an opportunity to learn and grow. You are expected to take ownership and consistently deliver quality work that drives value for our clients and success as a team. As you navigate through the Firm, you build a brand for yourself, opening doors to more opportunities.

Skills

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Apply a learning mindset and take ownership for your own development.
• Appreciate diverse perspectives, needs, and feelings of others.
• Adopt habits to sustain high performance and develop your potential.
• Actively listen, ask questions to check understanding, and clearly express ideas.
• Seek, reflect, act on, and give feedback.
• Gather information from a range of sources to analyse facts and discern patterns.
• Commit to understanding how the business works and building commercial awareness.
• Learn and apply professional and technical standards (e.g. refer to specific PwC tax and audit guidance), uphold the Firms code of conduct and independence requirements.
  
  

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 Science team you are expected to build machine learning models in cloud environments. As a Associate you are expected to leverage your knowledge in supervised and unsupervised machine learning algorithms, mentor junior team members, and confirm the delivery of top-quality data analysis. You are expected to prepare data for machine learning use cases, use visualization tools, and guide teams in programming.

Responsibilities

• Build machine learning models in cloud environments
• Utilize specialized knowledge in supervised and unsupervised machine learning algorithms
• Mentor junior team members
• Verify top-quality data analysis delivery
• Prepare data for machine learning use cases
• Use visualization tools to present data
• Guide teams in programming
  
  

What You Must Have

• Bachelors & Master Degree in Computer Science, Engineering, Econometrics, Statistics, Business Analytics, Informatics
• 2 years of experience
• Oral and written proficiency in English required
  
  

What Sets You Apart

• Experience in building ML models in cloud environments (At least 1 of the 3: Azure ML, GCPs Vertex AI platform, AWS SageMaker)
• Thorough knowledge and experience of supervised, unsupervised machine learning algorithms
• Thorough knowledge of statistics
• Experience in Data analysis
• Experience in machine learning frameworks and tools
• Advanced level programming in SQL or Python/Pyspark
• Proficiency with visualization tools
• Working knowledge of containerization, Dockers and data pipeline orchestration

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