Strategic Planning Manager

OUR IMPACT Corporate Planning & Management (CPM) unifies Finance & Planning, Global Procurement, Product & Reporting and CPM Engineering teams to deliver business planning and analytics, expense management, third party risk management, sustainability strategy for our operations and supply chain, and governance strategies across the firm. CPM Engineering provides engineering solutions that enable the firm to manage third-party spend & risk management, plan budgets, forecast financial scenarios, allocate expenses and support corporate decision making in-line with the firm's strategic objectives. Why does this role stand out: Direct business impact - your work shapes how the firm plans, spends, forecasts, and makes strategic decisions. Build enterprise-wide solutions that cross data and platform boundaries, and decision-support tools, not just isolated applications. Cross-functional exposure - partner closely with finance, procurement, product, and risk leaders across a global organization. Complex, meaningful problems - work on systems that improve transparency, controls, efficiency, and scalability across enterprise operations. We offer: The opportunity to work on high-impact platforms that directly influence firm-wide financial planning and operational resilience Access to modern cloud-native architectures , modern AI driven developer productivity tools ( Copilot, Claude Code etc ), distributed systems, and large-scale data pipelines A forward-looking environment where AI tools, agentic frameworks, and intelligent automation are actively shaping the next generation of our solutions A collaborative, global team where you can learn from experts and grow your career HOW YOU WILL FULFILL YOUR POTENTIAL Design, develop, and maintain software and data solutions across the entire software lifecycle from requirements gathering and architecture through implementation, testing and deployment Build responsive, intuitive experiences and robust services that power financial planning, expense management, and risk platforms Leverage AI tools and techniques (e.g., code-generation assistants, LLM-powered automation, prompt engineering, Spec-Driven Development) to accelerate development, improve code quality, and enhance platform capabilities Build and maintain knowledge graph and RAG systems to enable document and data retrieval, querying and searching Establish robust governance frameworks including logging, explainability, and auditability to ensure AI quality and reliability Collaborate globally with sponsors, users, and engineering colleagues across multiple divisions to create end-to-end solutions that meet complex business requirements Participate in code reviews to ensure quality, maintainability, and adherence to engineering best practices Take technical ownership of features and components, managing multiple stakeholders and driving delivery within a global team Stay current with the latest advancements in AI/ML platforms, tools, and software engineering practices to continuously improve our solutions QUALIFICATIONS Required Bachelor's or master's degree in Computer Science, Computer Engineering, Data Engineering or a similar field of study. 3+ years of proficiency in using programming languages (Java, Python etc ) to solve data science problems. Data Science & Engineering - experience using industry-standard libraries (e.g., Pandas, NumPy, PySpark, TensorFlow/PyTorch) to build scalable data pipelines, perform data modeling, and enable enterprise insights on large, complex datasets. Strong analytical and problem-solving skills - experience with algorithms, data structures, and software design Familiarity in utilizing AI tools for software development (e.g., AI-assisted coding, code review tools, LLM-based productivity tools) Foundational understanding of AI and agentic systems - familiarity with concepts such as large language models, prompt engineering, retrieval-augmented generation (RAG) etc. Comfortable with technical ownership, managing multiple stakeholders, and working as part of a global team Preferred - Experience That Can Set You Apart GenAI & Intelligent Data Retrieval using vector databases, embedding models, and agentic frameworks (e.g., LangChain) - to enable intelligent querying and synthesis of insights across large enterprise data assets. Experience with Distributed Databases & Search Platforms - building and optimizing scalable, distributed data systems (e.g ElasticSearch, OpenSearch) with a focus on indexing, query performance, and real-time data retrieval; familiarity with search relevance tuning, vectors and embeddings across large datasets. Advanced Data Analytics & Data Science experience applying data science methodologies - including statistical analysis, predictive modeling, and knowledge graphs - across diverse data types. Familiarity with MLOps practices including CI/CD for ML, model deployment, and monitoring Knowledge of cloud-native solutions (preferably AWS) Knowledge of the financial industry - corporate planning, expense management, or risk functions Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law. We are committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. #J-18808-Ljbffr