Position: Data Scientist / AI Engineer
Location: Irving, TX (Hybrid 3x in office)
Employment Type: Contract-to-hire
Contract Duration: 6 months-1 year
The Data Scientist is responsible for the design and development of advanced generative, recommender, and predictive models that will generate value creation. This role involves ensuring the performance and accuracy of solutions, staying abreast of the latest AI research and methodologies (particularly in the domains of natural language processing, predictive analytics, and information retrieval), as well as promoting and implementing data science best practices.
Responsibilities:
- Thought partner to the Head of AI and Product Manager at identify opportunities to unlock value in the industry
by leveraging distinctive AI expertise (machine learning and generative AI) to drive business solutions.
- Lead the design, development, validation, and deployment of innovative, performant, and scalable AI engines, applying rigorous testing to ensure alignment with business objectives.
- Conduct advanced statistical analysis to provide actionable insights, identify trends, and measure performance.
- Apply A/B testing framework to test models' quality and integrate data insights into the business processes.
- Coordinate with different functional teams to implement models, design processes and tools to monitor and analyze model performance and data quality.
- Drive the AI methodology R&D agenda to ensure CLIENT continues to offer added value by best-in-class AI approaches in a fast-moving landscape.
Key Skills:
DomainExpertise:
- MS/PhD(Computer Science or Electronics), or MS in Computer Applications, Economics, Statistics or Mathematics or related technical discipline
- 3+ years of deep applied expertise at developing and deploying complex AI/ML solutions, preferably in a
financial services context
- Heavy MS Azure Data Factory experience is a must.
- Strong and deep knowledge of a broad set of AI methodologies: Generative AI & Agentic AI, deep
learning, natural language processing, supervised learning (classification, regression), reinforcement learning
- Proficiency in Python is required together with multiple popular advanced analytics frameworks e.g.
pandas, spark, scikit-learn, langchain, langchain, llamaindex, tensorflow, pytorch
- Experience with popular cloud-based ML platforms (AWS SageMaker, Azure Machine Learning) is a plus
- Strong applied understanding of MLOps / LLMOps best practice
- Experience to merge and transform disparate internal & external data sets together to create inputs for AI
Agile +Digital Experience:
- Openness to working in Agile environments with multiple stakeholders
- Strong communication and collaboration skills to understand business partner needs and deliver solutions
Individual Skills:
- Professional attitude and service orientation; team player
- Quick learner to business needs and translates them into potential analytics solutions
- Strong analytical and problem-solving skills; healthy skepticism around the validity of data and its biases
- Good verbal and written communication skills
Mindset & Behaviors:
- Exemplary organizational skills with attention to detail & accuracy
- Ability to coach, mentor, and collaborate with business partners, analysts, and team members
- Attitude to thrive in a fast-paced environment, Open-minded to new approaches to learning