Hi everyone! 👋 I’m currently a Senior Product Manager at Eli Lilly (with 8 years of experience) and a background in building and scaling external/internal digital tools, driving cross-functional initiatives, and embedding operational excellence in highly regulated spaces. I’m now looking to pivot into the beauty and consumer space and would love to bring my product mindset to a company like Glossier or L’Oréal (or similar!). If anyone is able to provide guidance, please reach out. Thanks!

Working in erstwhile Dunn Solutions which has now merged with Kaar technologies Inc has been an incredibly enlightening experience. From starting as a simple PowerBI data analyst, I have had the opportunity to work on multiple technology stacks such as Azure, Microsoft Fabric, Snowflake, FiveTran and more. I have also worked in AI as well, since the nature of consulting enables us to be hands on with all the latest technologies. Look forward to many more learning experiences.

Looking for S/4HANA Technology Architect Consultant! You will play a crucial role in designing and delivering robust, scalable, and high-performing SAP solutions. You will be responsible for defining the overall architecture, ensuring seamless integration, and driving best practices in SAP S/4HANA implementations at our clients Ready to apply? Check out the job description first, then click the link to get started.https://https://lnkd.in/g-722qz3

As a Data Engineer with experience of ETL/ELT data end to-end pipelines high-quality, data across Insurance, Life, Health, Annuities, and Banking domains. Specialized in IBM DataStage, Snowflake, dbt, AWS and SQL to deliver data governance, secure, compliant, and regulatory needs. Experienced in Control-M, and DevOps CI/CD automated deployments, Linux-based operations and the responsible use of Generative AI tools.

As more EAs are being laid off in Silicon Valley, I’ve started learning ChatGPT and Google Gemini to stay marketable. I believe embracing A.I. tools can help us work smarter and increase our productivity. The future of administrative work is evolving, and I want to be ready for it. Is anyone else exploring A.I. tools or training? Let’s share resources and support each other through this transition

I’m a Software Engineer specializing in AI engineering, MLOps, and applied machine learning with experience across fintech, e- commerce, and data-intensive platforms. At Instacart, I lead the development of an AI-powered fraud detection system, productionizing ML models with PyTorch, scikit-learn, vector databases (FAISS/Pinecone), and MLOps pipelines (MLflow, W&B, Docker, AWS).

I’m a Software Engineer specializing in AI engineering, MLOps, and applied machine learning with experience across fintech, e- commerce, and data-intensive platforms. At Instacart, I lead the development of an AI-powered fraud detection system, productionizing ML models with PyTorch, scikit-learn, vector databases (FAISS/Pinecone), and MLOps pipelines (MLflow, W&B, Docker, AWS).

I’m a Software Engineer specializing in AI engineering, MLOps, and applied machine learning with experience across fintech, e- commerce, and data-intensive platforms. At Instacart, I lead the development of an AI-powered fraud detection system, productionizing ML models with PyTorch, scikit-learn, vector databases (FAISS/Pinecone), and MLOps pipelines (MLflow, W&B, Docker, AWS).

I’m a Software Engineer specializing in AI engineering, MLOps, and applied machine learning with experience across fintech, e- commerce, and data-intensive platforms. At Instacart, I lead the development of an AI-powered fraud detection system, productionizing ML models with PyTorch, scikit-learn, vector databases (FAISS/Pinecone), and MLOps pipelines (MLflow, W&B, Docker, AWS).

I’m a Software Engineer specializing in AI engineering, MLOps, and applied machine learning with experience across fintech, e- commerce, and data-intensive platforms. At Instacart, I lead the development of an AI-powered fraud detection system, productionizing ML models with PyTorch, scikit-learn, vector databases (FAISS/Pinecone), and MLOps pipelines (MLflow, W&B, Docker, AWS).