Client Insights Analysis: Leverage data from internal and external sources, including customer surveys, complaints, and feedback, to identify key opportunities for improving the client experience.
Collaborate with Stakeholders: Work closely with business partners, technologists, product managers, and control partners to deploy data-driven solutions into production and ensure alignment with business goals.
Reporting and Visualization: Prepare and distribute comprehensive reports and visualizations that summarize key insights and trends to senior leadership, providing clear and actionable recommendations.
Develop Advanced Analytics Solutions: Research, develop, and implement machine learning models to solve real-world problems related to client service, including natural language processing (NLP), speech analytics, and time-series predictions.
Drive Continuous Improvement: Identify and implement process improvements to enhance the efficiency and effectiveness of client service operations, leveraging data to drive decision-making.
Knowledge Sharing: Participate in the knowledge-sharing community by staying up-to-date with the latest advancements in machine learning and data analytics, and sharing insights with the team.
Required Qualifications, Skills, and Capabilities:
Educational Background: PhD or MS in a quantitative discipline such as Computer Science, Data Science, Mathematics, Statistics, or a related field with significant industry or research experience.
Technical Expertise: Strong background in machine learning and deep learning methods, with hands-on experience using toolkits such as TensorFlow, PyTorch, NumPy, Scikit-Learn, and Pandas.
Analytical Skills: Excellent quantitative and analytical problem-solving skills, with the ability to synthesize and interpret complex data from various sources.
Communication Skills: Strong written and verbal communication skills, with the ability to effectively communicate technical concepts and results to both technical and business audiences.
Collaboration: Proven ability to work in a highly collaborative environment, with excellent stakeholder management skills and the ability to influence and drive accountability.
Project Management: Ability to manage multiple concurrent projects, prioritize tasks, and deliver results in a fast-paced environment.
Advanced Tools: Proficiency in SQL and experience with large data sets, as well as advanced Excel and PowerPoint skills for creating compelling presentations.
Platform Knowledge: Experience with Snowflake and Databricks platforms.
Visualization Tools: Knowledge of QlikView is beneficial, but Tableau is preferred.
Data Preparation Tools: Experience with Alteryx.
Programming Skills: Proficiency in Python is mandatory, with 3-5 years of experience and the ability to function daily in Python.
LLM Expertise: Understanding of Large Language Models (LLMs) and the ability to use LLMs for coding and NLP tasks.