Senior Analyst & Data Scientist

Strong verbal and written communication skills to present analytical findings clearly to senior leadership and stakeholders. - 4 to 7 years of experience in data analytics or business operations, preferably in a financial technology firm. - Advanced proficiency in Excel, including complex formulas and VBA Macro programming. - Proficiency in Python or similar scripting languages for data transformation, automation, and analysis. - Working knowledge of SQL for querying and managing structured datasets. - Experience with data visualization tools, particularly Power BI, for building dashboards and reports. - Experience with data mining, statistical analysis, and segmentation techniques. - Proven ability to conduct what-if and scenario analysis and communicate implications to non-technical senior stakeholders. - Hands-on experience in building AI-powered workflows, automation pipelines, or LLM-assisted tools. - Genuine intellectual curiosity about AI and a track record of applying it to operational problems. - Ability to balance medium to long-term analytical projects with day-to-day operational responsibilities. As an experienced Data Scientist professional in Arcesium's Business Operations team within the Client and Partner Development (CPD) organization, you will be responsible for working with large volumes of varied datasets spanning pricing, headcount, market research, and commercial performance. Your role involves translating this data into models, frameworks, and insights to drive decision-making. Additionally, you will be expected to draw principled conclusions from your analysis and present strategic recommendations to senior leadership. You will also play a crucial role in identifying AI-driven solutions to enhance team efficiency and contribute to the AI strategy for CPD. Collaboration with global CPD teams across various functions will be essential to execute complex projects and facilitate organizational growth through data-backed governance. Key Responsibilities:

Identify relevant data sources and collaborate with CPD stakeholders to collect, analyze, and interpret large structured and unstructured datasets. - Devise and apply algorithms and models to extract insights from data stores, conduct data and error analysis to improve model performance, and ensure data uniformity and accuracy. - Analyze data for trends and patterns, interpret outputs, draw principled conclusions, and present actionable narratives at the senior leadership level. - Implement analytical models and reporting frameworks end to end, from data ingestion to leadership-ready outputs. - Design and develop automation scripts and data pipelines to synthesize and structure data from diverse sources, aiming for zero-touch processes and maximizing efficiency. - Produce KPI dashboards and performance reports using historical data to provide insigh