Data Science Engineering Manager

Management Level

Job Description & Summary

Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member’s unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.

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

• Analyse and identify the linkages and interactions between the component parts of an entire system.
• Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
• Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
• Develop skills outside your comfort zone, and encourage others to do the same.
• Effectively mentor others.
• Use the review of work as an opportunity to deepen the expertise of team members.
• Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.

Job Summary:  

We are looking for a skilled and passionate Data Science Engineering Manager to join our team. In this role, you will work at the intersection of data engineering and data science, designing scalable systems for data collection, analysis, and machine learning model deployment. You will collaborate with cross-functional teams to unlock actionable insights and build data-driven solutions for our clients. 

Key Responsibilities: 

• Design and implement robust data pipelines to collect, clean, and process large volumes of structured and unstructured data. 

• Optimize data workflows and machine learning systems to ensure efficiency and reliability. 

• Work closely with data analysts, data scientists, and stakeholders to define data requirements and deliver actionable insights. 

• Contribute on AI projects using RAG and LLM. 

• Perform exploratory data analysis and contribute to the creation of predictive and prescriptive analytics. 

• Stay updated with the latest trends in data science, machine learning, and big data technologies. 

Qualifications: 

• Bachelor's or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. 

• Proficiency in programming languages such as Python, R, or Scala. 

• Strong experience with big data tools and frameworks (e.g., Spark, Databricks) and cloud platforms (e.g., AWS, Azure, Google Cloud). 

• Solid understanding of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). 

• Hands-on experience with SQL and NoSQL databases. 

• Knowledge of CI/CD pipelines and MLOps principles. 

• Excellent problem-solving skills and a keen eye for detail. 

• Strong communication skills and the ability to work collaboratively in a team environment. 

Preferred Skills: 

• Familiarity with advanced analytics techniques (e.g., NLP, computer vision). 

• Experience in software development practices and version control systems (e.g., Git). 

• Knowledge of data visualization tools (e.g., Power BI). 

Travel Requirements

Available for Work Visa Sponsorship?

Job Posting End Date