We are an Applied AI Delivery & Research Team placed within the corporate sector for solving Employee Experience, HR, and Operations problems, it is a centralized global team responsible for all aspects of workforce data strategy, analytics and reporting, data governance, and the development of artificial intelligence and machine learning (AI/ML)-based solutions.
As an Applied AI/ML Senior Associate within our dynamic team, you will apply your quantitative, data science, and analytical skills to complex problems. You will collaborate with various teams to design and develop data science solutions, maintaining a deep understanding of the business problem. Your responsibilities will include data wrangling, data analysis, and modeling. You will advise on optimal solutions and provide insights on challenger models. You will be involved in strategic projects across the firm, making a significant impact at a leading financial services firm. Your role will be pivotal in developing data-centric solutions that enhance the firm's bottom line.
Job responsibilities:
- Engaging with stakeholders and understanding business requirements.
- Developing AI/ML solutions to address impactful business needs
- Working with other team members to productionize end-to-end AI/ML solutions
- Engaging in research and development of innovative relevant solutions
- Documenting developed AI/ML models to stakeholders
- Coaching other AI/ML team members towards both personal and professional success
- Collaborating with other teams across the firm to attain the mission and vision of the team and the firm.
Required qualifications, capabilities, and skills:
- Advanced degree in analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis, Operations Research) and 3+ years of applied experience.
- Strong foundation in AI/ML and excellent problem-solving skills.
- Familiarity with LLMs and agentic frameworks, such as LangGraph and similar technologies.
- Experience in the application of AI/ML to a relevant field.
- Demonstrated practical experience in machine learning techniques, supervised, unsupervised, and semi-supervised
- Strong experience in natural language processing (NLP) and its applications
- Solid coding level in Python programming language, with experience in leveraging available libraries, like Tensorflow, Keras, Pytorch, Scikit-learn, or others, to dedicated projects
- Previous experience in working on Spark, Hive, and SQL.
Preferred qualifications, capabilities, and skills :
- Financial service background
- PhD in one of the above disciplines.