Lance W

Lance W Email and Phone Number

Machine Learning Engineer @ Wells Fargo
san francisco, california, united states
Lance W's Location
United States, United States
About Lance W

 Experienced Machine Learning Engineer with over 8+ years of expertise in designing, developing, and implementing machine learning solutions that enhance customer satisfaction and contribute to business growth. Developed a prototype using GPT-3 for generating high-quality, engaging content drafts, which expedited content creation and enriched the editorial process. Led the integration of AI-driven tools to automate the analysis and generation of data-driven journalistic content, enhancing productivity and content accuracy. Explored the potential of generative adversarial networks (GANs) to generate synthetic data for training machine learning models where real data was scarce or sensitive, ensuring privacy compliance and model robustness. Demonstrated strong proficiency in Python, machine learning frameworks (TensorFlow, PyTorch), and big data technologies (Hadoop, Spark). Demonstrated success in leading teams to enhance business operations through data-driven decision-making and predictive analytics. Integrated state-of-the-art technologies such as generative AI and large language models to refine product offerings and personalize customer experiences. Developed predictive models, real-time analytics systems, and personalized customer engagement strategies. Demonstrated leadership in guiding teams through successful project executions and adept at translating technical details into actionable insights for stakeholders. Committed to continuous learning and applying the latest advancements in AI, such as Generative AI and Large Language Models, to maintain competitive advantage and innovation. Proven leadership in integrating cutting-edge technologies like natural language processing, time series analysis, and cloud-based solutions into scalable projects. Adept at transforming complex datasets into actionable insights and strategic business initiatives. Conducted extensive data analysis to understand user behavior, which informed new product features and enhancements.

Lance W's Current Company Details
Wells Fargo

Wells Fargo

View
Machine Learning Engineer
san francisco, california, united states
Website:
wellsfargo.com
Employees:
246787
Lance W Work Experience Details
  • Wells Fargo
    Machine Learning Engineer
    Wells Fargo Aug 2023 - Present
    San Francisco, California, United States
     Developed and implemented a real-time fraud detection system using machine learning models, reducing fraudulent transactions by 30%. Led a team that integrated predictive analytics into customer service platforms to personalizecustomer interactions and increase customer satisfaction. Collaborated with the IT and data warehousing teams to streamline data collection and preprocessing, enhancing the performance of analytics models. Utilized Generative AI for automated customer response generation, improving response timesand satisfaction rates. Initiated and led a pilot project on the application of Large Language Models (LLMs) forenhancing risk assessment tools, which improved the prediction accuracy of credit defaults. Published research on the application of AI in risk assessment, presented findings at severalindustry conferences. Utilized natural language processing techniques to analyze customer feedback, leading toimprovement in customer service ratings. Developed predictive models to assess credit risks, reducing financial losses through identification of key risk factors in loan approval processes. Applied time series analysis to forecast financial trends, assisting the treasury with asset management and investment strategies. Regularly presented insights and strategies to stakeholders, translating complex data findingsinto understandable business terms to support strategic planning. Kept abreast of industry trends and technologies by attending workshops and certifications inadvanced analytics and machine learning applications.
  • Ebay
    Data Scientist / Machine Learning Engineer
    Ebay Aug 2022 - Jul 2023
    San Jose, California, United States
     Developed machine learning models to predict market trends and optimize eBay's pricingstrategies and inventory management. Used Python for main development and R for statistical analysis. Utilized Redshift for data warehousing and PostgreSQL for transactional databases. Deployed models and manage data using AWS services like SageMaker for model training, S3for data storage, EC2 for computing resources, and Redshift for analytics. Integrated natural language processing to improve search functionalities and productcategorizations, significantly enhancing user experience. Tracked and managed project milestones using Jira and Rally to ensure agile project execution. Used Tableau for creating dynamic reports and dashboards to visualize the results of dataanalysis and model predictions. Focussed on Data Mining, Machine Learning, Data Visualization, Analytics, AI, Model Building,Data Ingestion, and Feature Engineering. Employed both supervised and unsupervised learning methods including regression (linear andlogistic), decision trees, bagging, XGBoost, KNN, Naïve Bayes, and PCA. Utilized TensorFlow, Keras, TFX, and PyTorch for developing and deploying deep learning models. Leveraged Scikit Learn, Pandas, Numpy for data manipulation, along with Jupyter Notebookand Spyder as development environments. Developed and refine algorithms for feature extraction and dimensionality reduction to improve model accuracy. Continuously test and refine models using real-world data and feedback loops to enhanceperformance. Worked closely with data engineers, business analysts, and other stakeholders to integratemachine learning solutions effectively.
  • Business Insider
    Data Scientist / Machine Learning Engineer
    Business Insider Apr 2020 - Aug 2022
    New York, United States
     Implemented advanced analytics that increased content engagement by 30% throughoptimized targeting and personalization. Developed predictive models using machine learning algorithms to forecast user behavior andtrends, significantly improving the accuracy of targeted marketing campaigns. Designed and analyzed numerous A/B testing frameworks to evaluate the impact of differentcontent strategies, enhancing user engagement rates. Deployed machine learning models into production, using Python and Spark to process andanalyze large datasets in real-time. Worked with big data technologies including Hadoop and Spark to handle complex dataprocessing tasks for enhanced decision-making. Created dynamic dashboards and reports using Tableau and Power BI to visualize businessmetrics for stakeholder presentations. Team Collaboration: Led a team of junior data scientists and analysts to build and implementscalable data models for strategic initiatives. Business Strategy: Worked closely with the marketing and business strategy teams totranslate data insights into actionable, quantifiable plans that drove content and advertisingrevenue growth.
  • Waveaccess
    Python Backend / Ml Engineer
    Waveaccess Aug 2015 - Mar 2020
    Las Vegas, Nevada, United States
     Developed and deployed python backend systems and machine learning models for variousapplications, including predictive maintenance, customer segmentation, and demand forecasting. Collaborated with cross-functional teams to gather requirements, design scalable backendsolutions, and implement scalable data pipelines using technologies like Apache Spark, Hadoop, and AWS Glue. Utilized Python for data manipulation, model development, and deployment, leveraginglibraries such as NumPy, Pandas, Scikit-Learn, TensorFlow, and PyTorch. Also, libraries andframeworks such as Django and Flask for backend development. Integrated machine learning models with cloud services (AWS, Azure, GCP) and deployed themusing Docker containers and Kubernetes. Ensured model performance and scalability by implementing monitoring and optimizationstrategies. Also ensured backend systems' security and performance through regular testingand optimization.

Lance W Education Details

Frequently Asked Questions about Lance W

What company does Lance W work for?

Lance W works for Wells Fargo

What is Lance W's role at the current company?

Lance W's current role is Machine Learning Engineer.

What schools did Lance W attend?

Lance W attended The University Of Texas At Dallas.

Who are Lance W's colleagues?

Lance W's colleagues are Karyl Durano, Mark Houseman, Clssbb, Rico Mattison Jr., Joshua Abbre Ribo, Giovani Trinidad, Laurie M., Ashley Huang.

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