Data Scientist Machine Learning
Resume:
Nan Li
*************@*****.***
Summary
8+ years of experience as a data scientist / Quantitative Analyst experience with strong skillsets to drive business growth. Effective communicator that adept at collaborating with stakeholders to understand requirements and deliver valuable insights. Experienced in mentoring and leading data scientist team, ensuring the delivery of high-quality solutions. Proficient in fine-tuning open source LLMs, Machine Learning, MLOps, Python, Advanced SQL, Azure Synapse, Spark, PBI, Excel, Tableau, Dashboard Building, R, SSIS, Deep Learning.
Experience
Data Scientist at Microsoft - Launch Consulting LLC, Bellevue, WA 2017 - now
Collaborated with cross-functional teams to gather and understand clear business requirements.
Designed hypothesis testing and machine learning models, defining metrics and key features for evaluation.
Involved in MLOps in development, testing, evaluation and optimisation of models developed.
Fine-tuning ML models with open source LLMs.
Led and mentored a team of 5 data scientists and data engineers, consistently delivering high-quality output to clients.
Organized weekly team meetings, providing constructive feedback and coaching to enhance team performance and collaboration.
Implementing a Data Lake Strategy with Azure Synapse.
Utilized SQL queries to extract necessary data from various sources.
Created Python Pipelines for data preprocessing, handling missing data, encoding categorical variables, scaling numeric features, and splitting train/test sets.
Created and delivered Power BI dashboard to monitor and track the performance of ML metrics.
Managed machine learning models after production deployment.
Successfully delivered results to clients and actively sought feedback for continuous improvement.
Presented complex technical concepts and analytical findings to non-technical audiences in a clear and concise manner, effectively communicating the value of data driven.
Conducted education and quality assurance sessions for end-users after model deployment.
Consultant at Valve - Blueprint Consulting LLC, Bellevue, WA 2016 - 2017
Leveraged statistical models to predict seasonal headcount, providing valuable insights to support effective people management decisions and ensure optimal resource allocation throughout the year.
Designed and implemented machine learning models to evaluate customer service quality, utilizing customer service tickets data to identify trends and opportunities for enhancing customer experiences and service efficiency. Run Arima models on time series data to make tickets prediction.
Designed website AB tests, incorporating ML models to predict conversion rates and provide recommendations to the product and marketing teams for conversion rate optimization.
Proficiently created reports in TABLEAU and Excel, delivering critical key performance indicators (KPIs) to management and providing actionable insights for data-driven decision-making.
Mentored junior team members, sharing best practices, and providing guidance on data science methodologies and tools.
Received recognition from management for outstanding contributions to business growth, customer satisfaction, and operational efficiency.
Senior Quantitative Analyst at GREAT WALL Investment, Beijing, China 2013 - 2015
Developed and deployed sophisticated quantitative models to analyze the impact of macroeconomic factors on the Stock Market, providing valuable insights to guide investment strategies and decision-making.
Conducted comprehensive investigations into the relationship between inflation rates and other key economic indicators using advanced methodologies such as Granger causality, Vector Autoregression (VAR), Generalized Autoregressive Conditional Heteroskedasticity (GARCH), Markov Chain Monte Carlo (MCMC), and Multivariate Structural Vector Autoregression (MSVAR).
Extracted meaningful patterns from vast economic datasets, enabling the identification of macroeconomic trends and correlations that affect market performance.
Contributed to the development and maintenance of proprietary quantitative models, refining and improving model performance to enhance the accuracy and reliability of forecasts.
Education
Ph.D. on Quantitative Economics. Jilin University, Jilin, China
M.S. on Software Engineering. Jilin University, Jilin, China
B.S. on Computer Science. Jilin University, Jilin, China
Skills
Machine Learning (ML) Model Development and Evaluation
Azure Synapse, data Warehouse development and ETL (SSIS, Cube)
SQL Querying and Data Extraction
Python (Pandas, Scikit-learn)
Data Preprocessing and Feature Engineering
Machine Learning Model Management
Power BI/Excel/Tableau Dashboard building
Communication and Stakeholder Engagement
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