Lead strategic direction and growth of DBS's secured lending portfolio across Singapore, overseas, and commercial mortgage books.
Responsibilities
Formulate and execute comprehensive strategies for profitable growth across Singapore mortgage, overseas property financing, and commercial/industrial mortgage portfolios
Analyze macro market trends, interest rate environments, liquidity, and property markets in Singapore and key overseas regions to inform portfolio strategy
Identify, evaluate, and capitalize on new business opportunities to expand market share and enhance overall profitability
Drive budgetary achievement and growth targets for all three portfolios
Lead the full product lifecycle for secured lending offerings, from innovative proposition design to post-launch optimisation
Requirements
Bachelor's degree in Business, Marketing, Finance, or a related field
Intermediate level Applications Development Programmer Analyst responsible for application systems analysis and programming activities.
Responsibilities
Utilize knowledge of applications development procedures and concepts, and basic knowledge of other technical areas to identify and define necessary system enhancements
Identify and analyze issues, make recommendations, and implement solutions
Utilize knowledge of business processes, system processes, and industry standards to solve complex issues
Analyze information and make evaluative judgements to recommend solutions and improvements
Conduct testing and debugging, utilize script tools, and write basic code for design specifications
Requirements
Bachelor’s degree/University degree or equivalent experience
MiniMed is building a lean, high-leverage AI & Data Science team. We are looking for a Senior AI Engineer who builds AI capabilities hands‑on and sets the standard the rest of the team builds to.
Locations (6)
Atlanta, Georgia, United States
California, United States
Seattle, Washington, United States
Washington, United States
Boston, Massachusetts, United States
Principal Scientist II, AI-Guided Antibody Drug Conjugate Design
Lead the application of artificial intelligence and machine learning to the design of next-generation antibody-drug conjugates (ADCs).
Responsibilities
Develop and implement AI/ML models to guide ADC discovery and optimization, including target selection, antibody engineering, linker design, and payload selection.
Build predictive models for critical ADC properties, including stability, internalization, efficacy, pharmacokinetics, toxicity, and therapeutic index.
Apply generative AI, protein language models, and structure-based design approaches to create novel antibody formats and conjugation strategies.
Integrate sequence, structural, biophysical, chemical, and biological datasets to accelerate iterative design-build-test cycles.
Inform engineering of monoclonal antibodies and advanced biologic formats to improve affinity, selectivity, internalization, developability, and manufacturability.
AI Outcome Customer Engineer supporting enterprise AI solutions on Google Cloud, bridging presales and post‑sales, leading technical delivery and orchestration.
Responsibilities
Lead technical delivery strategy and orchestration
Debug systems and collaborate with product and engineering teams
Design and integrate AI/ML models, APIs, ECM, ID, and cloud infrastructure
The Director of People Analytics and Workforce Intelligence will lead our global workforce intelligence strategy, transforming complex talent and organizational data into actionable business outcomes. Bridging HR, Artificial Intelligence, and enterprise analytics.
Locations (2)
Madison, Wisconsin, United States
United States
Responsibilities
Define and execute the global roadmap for People Analytics, aligning workforce insights directly with core business strategy and growth goals.
Lead the design, development, and deployment of custom AI-driven analytics tools, internal dashboards, and predictive decision-support applications for leaders and managers.
Shift the organizational paradigm from reactive, descriptive reporting to proactive, predictive talent interventions (e.g., flight-risk modeling, workforce planning, skill gap forecasting, performance drivers).
Utilize Generative AI frameworks across HR data ecosystems to automate insights generation, summarize employee sentiment, and streamline talent operations.
Salary ranges for U.S (excl. PR) locations (USD):$112,000.00 - $190,000.00
For roles located in California, Seattle WA, Washington DC, Boston MA, and New York City, the salary range is $124,000.00 - $212,000.00
Responsibilities
Prototype fast. Demonstrate “proof of life” for AI/ML models, agents, and tools against real MiniMed business problems, working from the business’s actual data and workflows rather than a sanitized sandbox.
Take it to production and drive adoption. Build, evaluate, and deploy on the MIA stack (Databricks, LangGraph/LangSmith, enterprise agent platforms), applying evaluation-driven development, guardrails, and deployment patterns so what ships is reliable, auditable, and maintainable.
Integrate into the enterprise environment. Wire agents and models into the surrounding systems — APIs, identity and access (SSO/SAML/OAuth), systems of record such as Salesforce and SAP, and enterprise data pipelines — so capabilities work against real, messy production systems rather than in isolation.
Set the technical standard. Establish reusable patterns for agent design, tool-calling, retrieval, and evaluation harnesses; review and quality-gate the work of other engineers on the team so the bar holds without a manager in the loop.
Feed learnings back to the platform. Turn what you learn in the field into improvements to the MIA platform, shared tooling, and reusable-pattern roadmap, so each deployment makes the next one faster.
Requirements
Bachelor's degree
Nice to have: Advanced degree
Nice to have: Experience leading or directing other engineers
Nice to have: Stakeholder-facing communication
Nice to have: Forward-deployed or embedded engineering
Partner with IT, Enterprise Data, and Security teams to ensure rigorous data governance, privacy compliance (GDPR/CCPA), and ethical AI frameworks for employee data.
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