Advisory Ai Engineer | Watsonx Team
CurrentMember of watsonx Client Engineering team. Working on Generative AI use cases and solutions. Building and tuning Foundation Models (IBM models, Hugging Face models, etc.).
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@ibm.com
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Daniel Fleck is listed as Advisory AI Engineer @ IBM | Generative AI | watsonx at IBM, based in Raleigh, North Carolina, United States. AeroLeads shows a work email signal at ibm.com, phone signal with area code 800, and a matched LinkedIn profile for Daniel Fleck.
Daniel Fleck previously worked as Advisory AI Engineer | Watsonx Team at Ibm and Advisory Data Scientist | Financial Services Market Data Science Team at Ibm. Daniel Fleck holds Bachelor Of Arts (B.A.) Public Policy, Minor: Mathematical Decisions Science from University Of North Carolina At Chapel Hill.
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As an Advisory AI Engineer at IBM, I leverage my expertise in Large Language Models (LLM) and Generative AI to deliver innovative and impactful solutions for clients across various industries. With over six years of experience in data science and machine learning, I have developed and deployed multiple machine learning and deep learning models and pipelines that enhance user experience, optimize business processes, and generate actionable insights.I enjoy collaborating with client executives and stakeholders to understand their challenges and goals, and to design and implement customized strategies and roadmaps for software services adoption. I also help lead and support the development and planning of AI solutions and tools that accelerate model performance analysis and ensure responsible and ethical AI practices. My mission is to help clients achieve success and satisfaction with IBM's cutting-edge technology and services.
Listed skills include Microsoft Excel, Public Speaking, Research, Microsoft Office, and 38 others.
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Armonk, New York, Ny, Us
Member of watsonx Client Engineering team. Working on Generative AI use cases and solutions. Building and tuning Foundation Models (IBM models, Hugging Face models, etc.).
Armonk, New York, Ny, Us
• Developed a patent-pending autocomplete search process trained on private data using TF-IDF vectorization, natural language understanding and caching to increase autocomplete speed to ~200-400 ms within an application• Deployed pycaret and text classification models on Azure Databricks using MLFlow and Azure ML to deploy as an Azure Kubernetes web service and monitor using IBM’s Watson OpenScale
Armonk, New York, Ny, Us
• Developed automated pipelines of training data metrics, and model training metrics, with IBM AI Factsheets that led to 4x time savings for the client in developing their Model Risk Management Reports• Brainstorm and scope machine learning use cases with client executives and develop a strategy roadmap for use case and IBM services implementation and adoption• Convey business insights and deliverables of machine learning use cases efficiently in executive readouts • Help lead development and planning of a model inspection toolkit package for accelerated model performance analysis
Armonk, New York, Ny, Us
• Automated a manual process for data cleansing and feature development for staffing optimization into a scalable ETL pipeline between Cloud Pak for Data and Snowflake using Python and SQL to save 10-12 hours weekly• Created and deployed an interactive R Shiny app on IBM Cloud using Kubernetes that develops visuals querying from MongoDB, and scores a staff optimization model based on inputs returning real-time logs and the final staff schedule • Designed and presented a system architecture plan for secure Microsoft Azure Active Directory authentication between Snowflake and IBM Cloud Pad for Data using OAuth• Member of a 3 person team whose client win was approved as a session for IBM’s biggest client conference, IBM Think 2021• Developed a machine learning pipeline in IBM Cloud Pak for Data using Python for a gradient boosting regression model that increased acceptable predictions of 2, and 3 months forward staff planning by 45%
Armonk, New York, Ny, Us
• Presented key findings to clients in a thorough and concise method to portray business impact• Explored deep learning classification methods using keras and tensorflow in Python for anomalous IP address detection and deployed a model with a wrapper function for a cybersecurity client• Completed unsupervised clustering and analysis using pyspark and IBM Watson Machine Learning Accelerator on parquet datasets to develop unique customer personas for a utility company
Boston, Ma, Us
• Scrum team member on Fidelity’s Enterprise Technology Risk Management team for the audit of their internal OpenStack Cloud Computing software using Agile auditing methodology• Develop an understanding of IaaS management, security, and governance while engaging in all audit planning, client meetings, and audit presentations, and documented all audit testing in work papers• Complete data analysis for audit testing of user access, and vulnerability management using Python and Power BI• Execute ad hoc requests including REST API querying the telemetry backend with Elasticsearch, and outlier detection of employees within the same active directory group using unsupervised learning in cluster analysis
Wilmington, Nc, Us
• Competed in the Kaggle NCAA March Madness Machine Learning (ML) Competition developing a predictive algorithm to predict the winner of every game using feature selection with ML models xgboost, logistic, and MLP
Durham, Nc, Us
• Reviewed SQL reporting with IT to ensure accuracy of new monthly IBNR reporting, reconciling any IBNR claims differences between our accounting and managed care systems• Liaised between Business Operations and IT on any business intelligence data, reporting or development needs• Collaborated with cross-departmental units to identify information needs and design solutions using business intelligence (BI) concepts to create parameter driven reporting
Durham, Nc, Us
• Created monthly reports on the status of Alliance’s Medicaid per member cost and presented findings to leadership• Utilized Microsoft Access to develop and define the monthly Medicaid reconciliation process• Communicated with Providers to develop Medicaid rates and implemented new programs and services• Analyzed individual enhanced rate requests submitted by providers to determine accuracy of their financial data
• Designed and developed weekly Tableau reporting for manufacturers to analyze the performance of their products within each category • Forecasted POS and presented findings to Advance’s team during category reviews in order to make educated product, category and promotional decisions• Performed ad hoc reporting and exploratory data analysis utilizing Advance Auto Parts Oracle BI Database for manufacturers and Advance Auto management
Boston, Ma, Us
• Worked in Salesforce analyzing internal data with outside data sources and other key metrics to provide lead generations for our fundraising team.• Created ad hoc reports for the fundraising and marketing teams analyzing their activity, and developed live dashboards as a Salesforce administrator. • Developed the scoring sheet for the Fundraising team's Summer Sales Contest, and created the weekly and biweekly reports.• Met with members of the Analytics team, along with other members of Fidelity Charitable frequently on daily and weekly projects focusing on lead generation.
Chapel Hill, Nc, Us
• Contributed to building the project's database of more than 4800 companies within the Research Triangle with information on company awards, grant funding, mergers, acquisitions, and other company history. • Created a database of 180 firms with a UNC connection to study the University’s impact on entrepreneurship in the RTP.• Met, interviewed and documented meetings with 15 founders with a connection to UNC who developed a successful start-up in the RTP.• Developed a 30-page report on UNC entrepreneurs’ experiences and views on the University's entrepreneurial ecosystem and it's impact on entrepreneurship in the RTP.
Chapel Hill, North Carolina, Us
•Synthesized market reports and gathered market data on Pharmaceutical R&D and clinical trial data in MatLab.•Made projections on future Pharmaceutical R&D, clinical trial testing, patenting, and overall efficiency trends.
Durham, Nc, Us
•Input transaction entries and new customers in the customer service database. •Finalized daily sales credit card balance sheets for inventory and financial records. •Created and maintained master spreadsheet of sales history and analyzed the change in product sales and yearly trends in transactions.•Demonstrated leadership and quick understanding of company mission leading to promotion from unpaid intern to paid staff member.•Assisted with the transition period for the new customer service database by switching over customer records.
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Daniel Fleck works for IBM.
Daniel Fleck is listed as Advisory AI Engineer @ IBM | Generative AI | watsonx at IBM.
AeroLeads has found 2 work email signals at @ibm.com for Daniel Fleck at IBM.
AeroLeads has found 1 phone signal(s) with area code 800 for Daniel Fleck at IBM.
Daniel Fleck is based in Raleigh, North Carolina, United States while working with IBM.
Daniel Fleck has worked for Ibm, Fidelity Investments, University Of North Carolina At Wilmington, Alliance Behavioral Healthcare, and Josco.
You can use AeroLeads to view verified contact signals for Daniel Fleck at IBM, including work email, phone, and LinkedIn data when available.
Daniel Fleck holds Bachelor Of Arts (B.A.) Public Policy, Minor: Mathematical Decisions Science from University Of North Carolina At Chapel Hill.
Daniel Fleck is listed with skills including Microsoft Excel, Public Speaking, Research, Microsoft Office, Powerpoint, R, Microsoft Access, and Microsoft Word.
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