Service Delivery Center, AI & Data - Analyst

EY•Dallas, TX

1d•$46,700 - $108,100•Hybrid

About The Position

EY's Financial Services Office (FSO) has Service Delivery Centers staffed by high-performing US-based resources who collaborate with experienced client-serving professionals. These centers deliver project-based work and managed services to US-based Financial Services clients. The role focuses on leveraging data to help financial institutions operate more efficiently and uncover new opportunities. You will solve complex problems and deliver AI and data solutions to clients, with significant growth opportunities and a focus on continuous learning and skill development.

Requirements

A bachelor's or master’s degree in computer science, information systems, or related technology majors.
Minimum of 1 years of related work experience in AI/ML engineering or MLE/ML Ops.
Proficiency in Python programming and associated machine learning libraries/packages (sklearn, TensorFlow, PyTorch, etc.).
Experience in applications of Neural Network architectures to Natural Language Processing, Computer Vision, and Machine Intelligence.
Knowledge of cloud-based AI services and machine learning platforms such as AWS SageMaker, Google AI Platform, or Azure Machine Learning.
Familiarity with containerization and orchestration technologies (Docker, Kubernetes) for deploying and managing AI applications in the cloud.
Good written and verbal communication skills.
A willingness and ability to travel at 0%-25%.
Valid driver’s license in the US.
Valid passport.
Passion for technology.
Understanding of data and comfort analyzing or manipulating it while generating reports for clients.
Ability to clearly articulate both problems and proposed solutions.
Willingness to learn and quickly adapt to changing requirements.
Team player and hard worker.
Not afraid to take initiative to master their craft and produce high-quality work.
Proactive approach.

Nice To Haves

Certification in any database management system, reporting or data visualization, or programming/statistical language.
Working knowledge or certifications in cloud technologies such as Snowflake, Databricks, AWS, or Azure.
Experience with generative AI models and techniques, including GANs and Transformers.
Understanding of the ethical implications of generative AI and commitment to responsible AI practices.

Responsibilities

Working with diverse teams of professionals with different skill sets to deliver a wide range of AI and data services.
Being a team player with great communication skills and the desire to learn technical skills.
Collaborating with diverse skills and backgrounds.
Fostering an innovative and inclusive team-oriented work environment.
Being accountable for the success of your team and the project’s components.
Building strong relationships with your internal clients.
Designing, building, and maintaining production-grade ML and DL models, machine learning workflows, and pipelines.
Helping clients make data-driven decisions by working with structured and unstructured data sets and building out predictive models.
Applying advanced analytical and statistical methods, including machine learning and data structure design.
Building and applying data analysis algorithms (data mining, statistics, machine learning, natural language processing, etc.) as appropriate.
Designing and developing solutions leveraging big data technology (Hadoop, Spark, etc.) to ingest, process, and analyze large, disparate data sets.

Benefits

Competitive compensation package based on performance.
Medical and dental coverage.
Pension and 401(k) plans.
A minimum of 15 days of vacation plus ten observed holidays and three paid personal days.
A range of programs and benefits designed to support your physical, financial, and social well-being.
Opportunities to develop new skills and progress your career.
Support and coaching from engaging and knowledgeable colleagues.
A collaborative environment.
Excellent training and development prospects.
Flexible vacation policy.
Time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence.