Yuning Liu Email & Phone Number

Seattle, Washington, United States

• Buying a home does not have to feel complicated. Our simplified approach helps you search, buy, and move in—all without having to stumble through the traditional process. We brought our local experts together, giving.
• Worked as Data Engineer in extraction data and preparing data according to business requirements.
• Used Pandas, NumPy, Seaborn, Tensorflow, Pytorch, Matplotlib, Sci-kit-learn, and NLTK in Python for developing data pipelines and various machine learning algorithm
• Employed statistical methodologies such as A/B tests, experiment design, and hypothesis testing.
• Implemented Apache Airflow for authoring, scheduling, and monitoring Data Pipelines
• Worked with commercial data mining tools such as R and Python depending on job requirements.

Seattle, Washington, United States

• The project involves developing an Internet traffic scoring platform for ad networks, advertisers, and publishers. The platform would use a combination of rule-based algorithms, site scoring, keyword scoring, lift.
• Gathered requirements based on the business problem, and developed and implemented advanced analytics including optimization, prescriptive analytics, and machine learning algorithms using Python, SQL, and Rest API.
• Involved in Data Manipulation & Visualization, Web Scraping, Machine Learning, Deep learning, Python programming, SQL, GIT, Unix Commands, NoSQL, MongoDB, and Hadoop.
• Involved in Setting up storage and data analysis tools in Amazon Web Services cloud computing infrastructure.
• Used pandas, NumPy, seaborn, scipy, Pytorch, matplotlib, Scikit-learn, and NLTK in Python for developing various machine learning algorithms.
• Used A/B testing, multivariate testing, and conversion optimization techniques across digital platforms.

Seattle, Washington, United States

• Our project was to design and develop an Enterprise Reporting System for financial services, to support the portfolio management and performance analysis of the Credit Card business with various reward offerings, and.
• Involved in gathering, analyzing, and translating business requirements into analytic approaches.
• Worked with Machine learning algorithms like neural network models, Linear Regressions, SVMs, and Decision trees for the classification of groups and analyzing most significant variables.
• Converted raw data to processed data by merging, and finding outliers, errors, trends, missing values, and distributions in the data.
• Developed near real-time data pipeline using spark
• Performed data analysis, visualization, feature extraction, feature selection, and feature engineering using Python.

Seattle, Washington, United States

• The goal of the project was to leverage data to improve their business strategy as well as transform their digital channel into an active business model that no longer is an expense but also helps businesses to save.
• Performing Data Validation /Data Reconciliation between disparate source and target systems for various projects.
• Identifying the Customer and account attributes required for MDM implementation from disparate sources and preparing detailed documentation.
• Performed data cleaning and feature selection using the MILib package in PySpark and working with deep learning frameworks.
• Prepared Data Visualization reports for the management using R.
• Used R machine learning library to build and evaluate different models.

Shanghai, China

• China CITIC Bank is an organization with a full range of products and services, focused on specialty program business. The major line of business is providing credit lines, overdrafts, and funds management. A Data.
• Aided Relationship Managers in conducting credit analysis on the syndicated term loans and revolving credit facilities for 11 public companies from different industries, including preparing executive summaries.
• Prepared credit application packages including financial analysis, financial projections, operating analysis, and industry analysis of corporate clients for the Head Office’s credit committee to review and approve
• Developed models to assess trends, project needs, surface challenges, and estimate costs
• Automated processes which reduced 50% of manual resources and doubled the efficiency
• Created pro forma cash flow projections in Excel to forecast clients’ operating revenue, expenses, and debt metrics and measure the clients’ repayment ability

• Used pandas, NumPy, Seaborn, SciPy, matplotlib, sci-kit-learn, and NLTK in Python for developing various machine learning algorithms.
• Participated in all phases of data mining; data collection, data cleaning, developing models, validation, visualization, and performed Gap analysis.
• Programmed a utility in Python that used multiple packages (SciPy, NumPy, pandas).
• Converted the data mart from Logical design to Physical design, defined data types, Constraints, and Indexes, generated Schema in the Database, created Automated scripts, and defined storage parameters for the objects.
• Performed Data cleaning process applied backward - Forward filling methods on a dataset for handling missing values.
• Defined various facts and Dimensions in the data mart including Fact fewer Facts, Aggregate, and Summary facts.

Master'S Degree, Business Analytics

Bachelor Of Science - Bs, Chemistry