Take a lead role in acquiring, managing and retaining meaningful relationships that deliver outstanding experience to our customers. In this role, you will balance your focus on business results by offering options and finding solutions to help our customers with issues.
As an Analytics Solutions Associate within the team, you will collaborate with LOB, Policy, Controls, and Technology teams to address business challenges through analytical solutions that promote measurable outcomes. You will conduct advanced statistical analysis and hypothesis testing to identify root causes and support strategic decision-making. Your role involves performing exploratory data analysis to uncover trends and provide actionable insights. You will design predictive and prescriptive analytics models using tools like Python, SQL, Alteryx, and Tableau. Leveraging AI/ML techniques, you will build models and systems to solve complex business problems. You will develop analytical frameworks for performance measurement and forecasting, and create data visualizations and dashboards for stakeholders. Your responsibilities include building data narratives and executive summaries for diverse audiences. You will conduct cohort analysis and A/B testing to optimize business initiatives. Additionally, you will design self-service analytics capabilities and apply statistical methods to solve business problems. Collaborating with data scientists and stakeholders, you will translate insights into strategic recommendations while staying updated on emerging trends in analytics and data science.
Job Responsibilities:
- Collaborate with LOB, Policy, Controls, and Technology teams to translate business challenges into analytical solutions that deliver measurable outcomes.
- Conduct advanced statistical analysis and hypothesis testing to identify root causes, validate assumptions, and support strategic decisions.
- Perform exploratory data analysis plus descriptive and prescriptive analytics to uncover trends, outliers, correlations, and anomalies that drive actionable insights.
- Design predictive and prescriptive models using Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn), SQL, Alteryx, and Tableau.
- Leverage AI/ML techniques to build classification, clustering, and recommendation solutions for complex business problems.
- Develop analytical frameworks for performance measurement, trend analysis, forecasting, and what-if scenario modeling.
- Create data visualizations and interactive dashboards that clearly communicate insights and enable data-driven decision-making.
- Craft data narratives and executive summaries that translate complex findings into clear, actionable recommendations for diverse audiences.
- Execute cohort analysis, customer segmentation, and behavioral analytics to identify optimization and growth opportunities.
- Measure initiative effectiveness through impact analysis and A/B testing to quantify business value and process improvements.
- Build self-service analytics capabilities and KPI monitoring frameworks that empower stakeholders with independent access to insights.
Required Qualifications, Capabilities, and Skills
- Hold a bachelor's degree or equivalent in Computer Science, Statistics, Data Management, Mathematics, or a related quantitative field.
- Bring 8+ years of experience in Data Analytics or Data Management with a track record of delivering impactful analytics solutions.
- Demonstrate strong SQL proficiency for querying and analyzing high-volume datasets.
- Apply Python programming for analytics using libraries such as Pandas, NumPy, Matplotlib, and related tooling.
- Deliver descriptive and prescriptive analytics that produce clear, business-relevant insights.
- Build interactive dashboards and reports using data visualization tools such as Tableau.
- Communicate effectively across levels, structuring complex problems, synthesizing insights, and presenting conclusions with risk-aware recommendations.
Preferred Qualifications, Capabilities, and Skills
- Apply advanced analytics techniques including statistical analysis, predictive modeling, and machine learning concepts.
- Implement AI/ML solutions in production, including training, validation, deployment, and monitoring.
- Demonstrate familiarity with KYC processes and relevant financial services regulatory requirements.
- Lead cross-functional analytics initiatives using strong project and stakeholder management skills.
- Use data governance frameworks and data management best practices to improve data quality and control.
- Employ Git-based version control and collaborative development practices.
- Operate effectively in Agile or Scrum delivery environments.
