Lead Data Science Consultant

Lead Business Execution Consultant

In this role, you will:

• Lead complex initiatives by utilizing data-driven, advanced analytical, statistical techniques, algorithms, or models to make actionable insights, trends, recommendations, including those that are cross-functional with broad impact acting as key participant in large-scale planning

• Review and analyze complex, multi-faceted, larger-scale, or longer-term business, operational, or technical challenges that require in-depth hypothesis generation and advanced analysis of multiple parts, including intangibles or unprecedented factors

• Make decisions in complex and multi-faceted situations requiring an expertise in analytical thinking to resolve abstract business issues that influence and lead broader work team to meet deliverables and drive new initiatives

• Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to drive recommendations and strategies based on data driven, analytical insights, trends, and patterns that will resolve issues and achieve goals; may lead projects, teams or serve as a peer mentor

• Execute complex analytical experiments and create innovative statistical models to discover solutions for abstract business problems across various domains

• Interpret and analyze data, using advanced analytics modeling methods and programming, to recommend ways to solve problems and influence business decisions and strategies

• Provide consultation to peers on data science best practices, methods, and tools to leverage

• Communicate actionable insights and recommendations using data in a digestible format to a non-technical audience of varying levels

Required Qualifications:

• 5+ years of data science experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Desired Qualifications:

• Lead complex initiatives using advanced analytical, statistical techniques, and models to deliver actionable insights across cross-functional domains

• Analyze large-scale, multi-faceted business and operational problems using hypothesis-driven and structured analytical approaches

• Drive decision-making in complex scenarios by leveraging deep analytical thinking and influencing stakeholders

• Collaborate with peers and senior stakeholders to develop and implement data-driven strategies

• Design and execute analytical experiments and models to solve business problems and uncover opportunities

• Interpret and analyze large datasets using SQL, Python, SAS, or similar tools to influence business decisions

• Communicate insights effectively to technical and non-technical audiences through executive-ready storytelling

• Support redress activities and impact analysis for identified control breaks

• Perform root cause analysis for exceptions and anomalies in control outputs

• Partner with stakeholders to quantify customer and financial impact and define remediation scope

• Ensure end-to-end traceability from issue $\rightarrow$ analysis $\rightarrow$ resolution $\rightarrow$ closure

• Own end-to-end execution of control reports (Self Assurance deliverables)

• Ensure timely, accurate, and complete delivery of all control outputs

• Perform rigorous pre- and post-run validations (data completeness, accuracy, reconciliation)

• Validate outputs against business rules, thresholds, and control intent prior to release

• Experience in Data Analytics, Insights, or Data Science

• Experience in Banking/Financial Services delivering analytical insights and recommendations

• Strong SQL and SAS skills required

• Proven experience in leading projects independently and mentoring junior team members

• Strong stakeholder management and ability to influence senior stakeholders

• Experience in: Data extraction, transformation, and analysis (Teradata, data warehouses)

• Data migration initiatives (Teradata/Hadoop to GCP)

• Python/PySpark for large-scale data processing

• Data validation, QA, and reconciliation processes

• Control assurance (SAA) and redress analytics (highly preferred)

• BI tools (Tableau / Power BI) and self-service analytics

• Strong communication skills with ability to present insights to business stakeholders

• Strong problem-solving skills with ability to handle ambiguity and multiple priorities

Job Expectations:

• Strong proficiency in SQL, Python, SAS, PySpark

• Experience with GCP and modern data platforms

• Exposure to machine learning techniques (forecasting, clustering, segmentation)

• Financial services domain expertise

• Highly organized and proactive with the ability to manage multiple deliverables

• Strong storytelling and visualization skills for executive audiences

• Ability to drive innovation using automation and emerging technologies (e.g., GenAI)

• Demonstrated persistence and accountability in meeting tight deadlines and compliance expectations