• AI-Augmented Data Practitioner: You actively leverage modern GenAI tools, conversational assistants, context engineering, and prompt design to supercharge analytics, code generation, and campaign operations.
• Campaign Orchestrator & Optimizer: You excel at translating complex business requirements into high-performance data extraction queries using SQL, PySpark, and Python , continuously refining targeting logic to maximize campaign conversion and ROI.
• Analytical Problem Solver: You apply structured analytical techniques—such as funnel diagnostics, test-versus-control lift analysis, and cohort evaluation—to uncover performance drivers and optimize marketing channels.
• Workflow Innovator: You proactively automate repetitive processes—using AI for Text-to-SQL generation, automated insight summarization, knowledge base curation, and content variant ideation.
• Disciplined & Version-Controlled: You manage analytical assets, queries, and automation scripts using Git / GitHub for robust code collaboration and version control.
• Process & Controls Oriented: You uphold strict campaign gating criteria, contact fatigue management, customer privacy regulations, and risk/compliance controls.

What You Do (Core Responsibilities)

1. Campaign Execution & Data Pipeline Management

• Partner with Wealth Product Managers, Marketing, and Relationship Manager (RM) teams to translate campaign objectives into robust technical targeting criteria.
• Develop, test, and execute data extraction queries and pipelines using SQL, PySpark, and Python to generate qualified lead lists.
• Enforce campaign gating, contact frequency rules, suppression logic (e.g., Do-Not-Contact lists, regulatory opt-outs), and eligibility filters across digital and RM channels.
• Manage end-to-end campaign delivery calendars, ensuring 100% on-time execution of scheduled and trigger-based wealth programs.

2. Campaign Analytics, Experimentation & Optimization

• Performance & Funnel Analytics: Analyze campaign engagement funnels (Targeted ➔ Delivered ➔ Engaged ➔ Converted ➔ Balance/NNA Impact) to diagnose drop-offs and identify growth opportunities.
• Experimentation & Lift Measurement: Design and execute test-versus-control experimental frameworks and A/B test splits to isolate incremental campaign lift and revenue impact.
• Targeting & Channel Optimization: Analyze response patterns across customer segments and delivery channels (Mobile App In-App/Push, Online Banking, Email, SMS, RM CRM) to recommend targeting refinements and channel mix optimization.
• Interactive Visualizations: Build and maintain interactive performance tracking dashboards and diagnostic tools in Tableau / Power BI with automated underlying data feeds.

3. GenAI Enablement, Context Engineering & Workflow Automation

• Context Engineering & Knowledge Base Setup: Organize, structure, and curate internal campaign rules, data dictionaries, and targeting playbooks into searchable knowledge bases to enable high-accuracy AI retrieval and team knowledge sharing.
• Retrieval Optimization: Optimize data retrieval contexts and prompt structures to ensure conversational AI and retrieval-augmented tools deliver precise, hallucination-free analytical outputs and code.
• Text-to-SQL & Natural Language Processing (NLP): Apply Text-to-SQL interfaces and NLP techniques to accelerate ad-hoc data exploration, query generation, and unstructured client feedback/interaction analysis.
• AI-Assisted Code Acceleration: Utilize GenAI coding tools to rapidly draft, optimize, and debug complex SQL queries, PySpark data transformations, and Python scripts.
• Automated Campaign Insights Summarization: Leverage GenAI pipelines to generate executive narrative summaries, performance commentary, and anomaly explanations from campaign outcome data.
• Content & Message Variant Ideation: Assist marketing partners by using Generative AI to generate personalized messaging copy variations, email subject lines, and RM talking point templates tailored to specific client segments.

4. Code Collaboration, QA & Data Governance

• Manage and version-control all campaign scripts, SQL queries, and configuration files using Git / GitHub .
• Perform thorough Quality Assurance (QA) validations—such as row count reconciliations, schema validations, null checks, and deduplication—before releasing leads to execution channels.
• Maintain comprehensive documentation of campaign metadata, targeting criteria, and data lineage.

Key Deliverables

• Target Audience Datasets / Leads: High-precision, fully validated target lead files delivered to digital execution engines and CRM platforms.
• Campaign Delivery Calendar: Well-managed schedule of recurring, trigger-based, and ad-hoc wealth campaign programs.
• Optimization & Lift Analysis Decks: Analytical performance decks isolating incremental conversion, Net New Assets (NNA), and channel efficiency.
• Interactive Performance Dashboards: Automated Tableau / Power BI dashboards for campaign funnel monitoring and stakeholder self-service.
• AI-Assisted Summaries & Knowledge Bases: Curated campaign knowledge bases, prompt templates, and automated executive performance briefs.
• Versioned Code Repository: Well-documented, reusable SQL, PySpark, and Python scripts maintained in GitHub.

Education & Experience

• Education: Bachelor’s degree in Computer Science, Information Technology, Engineering, Statistics, Mathematics, Economics, or related quantitative field.
• Experience: 5–8 years of hands-on experience in Campaign Analytics, Marketing Analytics, Business Intelligence, or Customer Data Operations within Banking / Financial Services (Wealth Management or Retail Banking preferred).

Technical, Analytics & Campaign Optimization Skills

• Database & Querying: Strong hands-on proficiency in SQL (complex joins, CTEs, window functions, and query execution plan optimization).
• Big Data & Scripting: Practical working knowledge of Python and PySpark for data manipulation, pipeline automation, and analytical dataset creation.
• Campaign Analytics & Optimization: Strong expertise in campaign performance diagnostics, test vs. control lift measurement, funnel conversion analysis, and targeting rule optimization.
• BI & Visual Analytics: Proven experience designing executive-level interactive performance dashboards in Tableau or Power BI .
• Version Control: Solid understanding and practical usage of Git / GitHub for code repository management, branching, and versioning.
• Platforms: Familiarity with enterprise campaign management tools (e.g., Covenant, Unica, Salesforce Marketing Cloud, Adobe Experience Platform) and Dataiku DSS is an advantage.

AI Knowledge & GenAI Productivity Skills

• AI Literacy & Foundations: Solid conceptual understanding of modern Artificial Intelligence, Large Language Models (LLMs), and Conversational AI capabilities.
• Context Engineering & Knowledge Base Setup: Experience setting up, organizing, and structuring domain knowledge bases, data schemas, and contextual documentation for AI-assisted workflows.
• Retrieval Optimization: Understanding of retrieval optimization techniques to feed relevant context into LLMs for accurate code generation and data querying.
• Prompt Engineering: Demonstrated ability to craft structured, multi-turn, and few-shot prompts for data analysis, code generation, and content drafting.
• Text-to-SQL & NLP: Practical familiarity with Text-to-SQL tools and Natural Language Processing (NLP) techniques for data extraction, schema querying, and text analysis.
• GenAI-Assisted Development: Experience utilizing AI coding tools to accelerate SQL/Python script writing, query refactoring, and automated debugging.
• AI-Driven Insights & Copy Generation: Practical experience using GenAI to summarize campaign outcome metrics into narrative insights and brainstorm personalized copy variations.

Soft Skills

• Excellent communication and stakeholder management skills with ability to translate business goals into analytical solutions.
• Strong problem-solving orientation with attention to detail, data accuracy, and regulatory compliance.

Proactive mindset with a keen interest in adopting and propagating modern AI productivity tools within the team

Decision Management ------------------------------------------------------

Data/Information Management ------------------------------------------------------

Full time ------------------------------------------------------

Most Relevant Skills

Please see the requirements listed above. ------------------------------------------------------

Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------

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