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Data Analyst Civil Engineering

Location:
San Jose, CA
Posted:
September 08, 2020

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Resume:

LI, YUEWEI Data Scientist, Data Analyst

*** ***** *******, *** ****, CA Phone: 281-***-**** Email: **********@*****.*** Open to relocate SUMMARY:

• Dedicated and detail-oriented Data Scientist, Analyst with 5 years of experience on building growth strategies, extracting insights from data, designing and executing A/B testings, creating machine learning models for driving efficient growth.

• Experience and ownership of full Machine Learning pipeline: data collection, feature engineering, model building, parameter tuning, deployments of classification, regression and clustering models.

• Created dashboards to identify the hidden key points and track all the important metrics and extract insights, understand the strengths and weaknesses at those points and come up with solution, then build models to improve KPI performance.

• Mainly focus on the engagement journey of all type of customers and built strategies for retention, revenue, sales and efficiency. Areas such as: Growth Models and strategy, Customer Engagement, Retention and Churn, Automation, Data Analysis and Metrics, Machine Learning Models, A/B Testing.

• Professional experience in business intelligence and marketing strategies, including deriving business insights, improving business growth and customer engagement. Outstanding written, verbal and presentation skills with strong analytical and problem-solving skills to address recommending solutions. Effectively communicate with external clients and internal teams to deliver solutions on time. TECHNICAL SKILLS:

Programming Languages: SQL, Python, R, SAS

Database:Relational: MySQL, SQL, MSSQL, PostgreSQL, NoSQL: MongoDB, DynamoDB, Cosmos DB Tools: MySQL, Jupyter Notebook, PyCharm, Weka, Workbench, R-Studio, Matlab, Looker, Salesforce Big Data: Hadoop(HDFS, HBase, MapReduce, Hive, Pig, Spark), AWS(Redshift, EMR, S3, Glue, RDS, EC2), GCP(Kubernetes, BigQuery), Microsoft Azure

ETL Tools: MS SQL BI(SSIS, SSAS, SSRS), AWS(GLUE, Redshift), Hadoop(HiveQL, SparkSQL), Informatica Statistics & Machine Learning: A/B test, Linear Regression,Time Series, Logistic Regression, PCA, SVM, Decision Tree, Random Forest, XGBoost, K-NN, K Means Clustering, CNN, RNN, DNN, NLP Cloud: AWS (EC2, S3, EBS, RDS, EMR, IAM, etc.), GCP (kubernetes), Microsoft Azure Data Visualization: Tableau, Python(Matplotlib, Plotly, Seaborn), R-Studio, Power BI, Chartio, Google Data Studio, Looker Others: basic & advanced MS Excel(formulas, Macros, Vlookup, VBA, Pivot tables), MS office, Teradata, Google Analytics EXPERIENCE:

Data Scientist, Analyst Beshton Software Inc. Santa Clara, CA May 2019 – Present

• The project is aiding the Client to make Customer centric decisions rather than current product centric approach. And segmented the customers based on their behavior in Tableau/Power BI and predicting Future value for the them and make plan to enhance revenue and enhance customer conversion rate .

• Developed scalable Tableau dashboards, SQL-based ETL pipelines to provide day-to-day metrics reporting and ad hoc data analysis.

• Created Power BI/Looker dashboards and performed EDA to uncover trading trends, identify key metrics and performance indicators(KPI) for predictions and analysis.

• Analyzed trends in categories, stores, distribution centers across service level, forecast accuracy metrics to identify product improvement opportunities.

• Applied statistical models(A/B test, Hypothesis test, regression) to understand customer preferences on the web page setup.

• Engaged in Python with Numpy, SciPy, Pandas, Scikit-learn, TensorFlow to load and process large-scaled data. Conducted feature engineering, model diagnosis, validation, adjust parameters by cross-validation to build machine learning models to make predictions.

• Monitor the product performance systematically to identify issues and share feedback with the development team. And made strategy conclusions, then reported to manager, and based on the feedback that the resulting customer conversion rate increased by 23%. Teaching Assistant University of Houston-Clear Lake Houston, TX Jan 2017 - Dec 2017

• Assisted instructor and provided support and guidance to students at weekly assignments, projects or course related questions.

• Worked with the instructor on small research projects to be assigned to the students. Data Analyst Chengdu Surveying Geo-technical Research Institute Co. Ltd of MCC Chengdu, China Jul 2012 - Jan 2016

• Conducted market research and analyzed customer data to draw insights and develop branding plans.

• Managed projects through the entire process including building growth strategies, extracting insights from data, designing and executing A/B testings, creating machine learning models for driving efficient growth.

• Improved clients’ business performance by drawing actionable insights in Tableau/Looker from customer data and campaign data, and deploying marketing and branding plans

• Increased click-through rate and conversion rate by conducting funnel analysis and A/B testing.

• Used Time series and ML models to forecast demand of dealers based on their order history, achieved an accuracy of 87.2%.

• Presented the result of teamwork to the executive clients. PROJECT:

USA crime analysis Jan 2018-May 2018

• Established a goal, collected data, cleaned crime data sets, educational proportion data set and personal income data set by Python .

• Using Neural Networks, MANOVA, Mann-Whitney to test the relationship between each moth by Python.

• Used Multinomial Logistic Regression, Time-Series Analysis, Clustering Analysis to analyse crime data set. Whether the factors that affect housing price and police station affect crime rate in Houston Aug 2018-May 2019

• Imported data of housing price from relational database and police station data set into R and combined crime data by address.

• Used Correlation Coefficient, Linear Regression, Backward Stepwise Regression, Factorial Design to find the influencing factors by R.

• Used Weka to perform decision tree to figure out which crime type does affect police station distribution.

• Used K-means Clustering, ANOVA, Chi-square test, Wilcoxon Rank Sum Test to analyse the data sets. EDUCATION:

University of Houston-Clear Lake Master of Science in Statistics 2017-2019 Chengdu University of Technology Bachelor of Science in Civil Engineering 2008-2012



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