The selected candidate
- Collaborates with senior data scientists to build, fine-tune, and evaluate generative AI models, including large language models (LLMs), for various applications.
- Implements data pipelines and workflows to gather, clean, and prepare data from diverse sources for analysis and model training.
- Works on developing and deploying machine learning algorithms, ensuring models are optimized for performance and scalability
- Assists in translating complex technical findings into actionable insights and recommendations for non-technical stakeholders, contributing to impactful business decisions
Your key responsibilities include
- Implementing AI solutions that integrate seamlessly with existing business systems to enhance functionality and user interaction.
- Reviewing complex data sets to establish data quality and highlighting where data cleansing is required to remediate the data
- Designing and implementing data models to manage data within the organization,
- Migrating data from one system to another using multiple sources, identifying and
- implementing storage requirements
- Analyzing the latest trends such as cloud computing and distributed processing, and their uses in business, building industry knowledge
- Peer reviewing models and working with relevant business areas to seek their input and ensuring they are fit for the designed purpose
- Automating important infrastructure for the data science team.
- Staying current with AI trends and suggesting improvements to existing systems and workflows.
Skills and attributes for success
- 5+ years’ experience in machine learning, large scale data acquisition, transformation, and cleaning, both structured and unstructured data
- Experience with generative LLM fine-tuning and prompt engineering.
- Good knowledge with cloud ecosystems, Azure is preferred
- Strong programming skills in Python and developing APIs
- Knowledge of containerization platforms like Docker is a must.
- Experience with Git and modern software development workflow.
- Experience with tools in the distributed computing, GPU, cloud platforms, and Big Data domains (e.g., GCP, AWS, MS Azure, Hadoop, Spark, Databricks) is a plus
- Experience in ML/NLP algorithms, including supervised and unsupervised learning.
- Experience with SQL, Document DBs and Vector DBs
- Batch Processing - Capability to design an efficient way of processing high volumes of
- data where a group of transactions is collected over a period Data
- Visualization and storytelling - Capability to assimilate and present data, as well as more advanced visualization techniques.
Education
- Bachelor in Artificial Intelligence, Analytics, Data Science, Computer Science, Engineering, Information Technology, Social Sciences or related fields preferred
What we look for
- Strong analytical skills and problem-solving ability
- A self-starter, independent-thinker, curious and creative person with ambition and passion
- Excellent inter-personal, communication, collaboration, and presentation skills
- Customer focused
- Excellent time management skills
- Positive and constructive minded
- Takes responsibility for continuous self-learning
- Takes the lead and makes decisions in critical times and tough circumstances
- Attention to detail
- High levels of integrity and honesty
EY 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.