About the job

Here at SGV, you'll have the chance to build a truly exceptional experience. We'll empower you with the latest technology, surround you with high-performing teams, and provide the global scale and diverse and inclusive culture you need to discover your full potential.

Our Technology Assurance professionals play an important role within Assurance. As companies continue to digitize and automate more aspects of their business, performing high-quality audits and providing other assurance services require deeper capabilities with specialized knowledge of auditing technology. Services provided include Financial Audit IT, other assurance services such as System and Organization Controls Reporting (SOCR) and Agreed Upon Procedures (AUP), and expanded assurance services such as pre-implementation assessments, readiness engagements and ISO certification services as well as integration with other Assurance competencies.

Job Summary

As an Associate in our Technology Consulting practice, you will play a vital role in supporting our clients technology initiatives. You will be hired into a specific competency, where you will gain hands-on experience and exposure to a variety of technologies and tools. This position is ideal for individuals who are eager to learn, adapt, and contribute to innovative projects in a collaborative environment. You will work closely with experienced professionals, gaining insights into best practices and industry standards.

Your key responsibilities

As an Associate within the Technology Consulting team, you must be able to perform the following:

Understand the problem: Help analyze business requirements and translate them into technical requirements. Clarify user needs, business objectives, constraints, and success criteria before choosing a technical approach.
Prepare and explore data: Use Python and SQL to clean, transform, and analyze data. Identify quality issues, patterns, and limitations, and support data validation across the data lifecycle.
Support data and AI foundations: Help build and maintain data pipelines and data models that support data storage, integration, and model development on the target platform design.
Build practical solutions: Implement simple baselines and suitable AI/ML approaches and compare them. Projects may involve prediction, clustering, recommendations, document intelligence, or knowledge retrieval.
Evaluate and improve: Choose relevant metrics with guidance, design appropriate validation, analyze errors, and measure how changes to data, representations, models, and parameters affect results.
Contribute to engineering delivery: Write readable, modular code. Debug issues, document experiments, and take part in code reviews. Under senior guidance, support integration, automated testing, CI/CD, and deployment to cloud or on-premises environments.
Explain results: Communicate assumptions, alternatives, trade-offs, limitations, and implications for users in clear language.
Work responsibly: Follow project requirements for data privacy, data quality, security, governance, and responsible AI. Raise uncertainty, unexpected behavior, and delivery risks early.

Skills and attributes for success

At the Associate level, we expect foundational, working knowledge of the following capabilities. You will deepen them through coaching and project experience.

Computer programming: Ability to write, test, and debug code, primarily in Python and SQL, that carries out data processing and modeling tasks.
Computational thinking: Ability to break down problems and express solutions as algorithms, code modules, and computational steps.
Statistics and operations research: Ability to apply core statistical, mathematical, and optimization concepts to analyze data and support business decisions.
Machine learning: Understanding of how to engineer features and train, validate, and test machine learning models, and how to improve them using data.
Deep learning: Foundational understanding of neural network architectures and how they are trained for different learning objectives.
Data architecture: Understanding of relational and dimensional data modeling concepts, and of how data is structured, integrated, and stored to support analytics and AI.
Cloud computing: Knowledge of core cloud computing concepts and components, such as compute, storage, networking, and managed AI services, that are used to build and run AI solutions.
Technical design optimization: Awareness of how to make code and models more efficient by reducing memory use and input/output operations and increasing execution speed.
XOps: Awareness of DevOps, DataOps, and MLOps practices across the solution lifecycle, including version control, automated testing, CI/CD, and monitoring.
Applied data science and data analysis: Ability to explore, interpret, and visualize data to generate insights and explain what they mean for the business.
Data quality, privacy, and governance: Awareness of the data quality checks, data privacy requirements, and governance policies that apply to data used in AI solutions.

To qualify for the role, you must have:

Bachelor's degree in computer science, statistics, mathematics, data science, engineering, or a related quantitative field, or equivalent skills you can demonstrate.
Ability to write and debug Python on your own for a small data or modeling task, with an understanding of functions, data structures, and basic algorithms.
Working knowledge of SQL, relational databases, and tabular data manipulation, including joins, aggregation, and handling missing or inconsistent values.
Sound foundations in probability, statistics, and linear algebra, with the ability to apply these concepts to data and explain what they mean in practice.
Understanding of core machine learning concepts, including supervised and unsupervised learning, features and representations, training and validation, overfitting, data leakage, and evaluation metrics.
Evidence of completing a data or ML project and explaining the problem, your contribution, the approach, the evaluation, and the limitations. Coursework and thesis projects count.
Structured problem-solving: the ability to break an unfamiliar problem into manageable steps, compare alternatives, test assumptions, and recognize when you need guidance.
Clear communication, openness to feedback, and willingness to learn through experimentation and collaboration.

Ideally, you'll also have:

Python libraries such as pandas, NumPy, and scikit-learn; deep learning frameworks such as PyTorch or TensorFlow; Git and collaborative development.
Natural language processing, image processing and analysis, speech and audio processing, embeddings, information retrieval, recommender systems, or document processing.
Generative AI: LLM applications, foundation models, retrieval-augmented generation, structuring content for AI use, and systematic evaluation of generated outputs.
AI platforms and tools, including cloud services such as Azure, APIs, containers, automated testing, CI/CD, and model deployment and scaling.
Responsible AI and AI governance concepts, such as model risk, fairness, transparency, and data privacy.

What we offer:

SGV offers a competitive remuneration package where you'll be rewarded for your individual and team performance. We are committed to being an inclusive employer and are happy to consider flexible working arrangements. Plus, we offer:

Continuous learning: You'll develop the mindset and skills to navigate whatever comes next.
Success as defined by you: We'll provide the tools and flexibility, so you can make a meaningful impact, your way.
Transformative leadership: We'll give you the insights, coaching and confidence to be the leader the world needs.
Diverse and inclusive culture: You'll be embraced for who you are and empowered to use your voice to help others find theirs.

SGV | Building a better working world.

SGV exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.

Working across assurance, consulting, law, strategy, tax and transactions, SGV teams ask better questions to find new answers for the complex issues facing our world today.

Associate AI/ML Engineer