SUMMARY

• Around 7+ years of experience as data analyst.
• Strong SQL skills in retrieving data.
• Fluency in programming language Python in Jupyter Notebook.
• Extensive experience in ETL data pipelines for extracting, transforming, loading.
• Excellent experience in designing dashboards with Tableau and Power BI.
• Experience with big data environment, Spark, Hive.
• Experience in AWS S3, Lambda, DynamoDB.
• Experience in machine learning, deep learning.
• Extensive experience in designing data pipelines for data collecting, cleaning, exploring, preprocessing, engineering, modeling.
• Experience in building models with Python for classification, regression, and clustering problems.
• Excellent skills in Excel to query, analyze, visualize, modeling data.
• Experience in formulatingLinear Programming model to find optimal configuration for production planning, inventory controling order to maximize profit with Excel (Solver).

TECHNICAL SKILLS

• SQL
• Spark
• Hive
• Data Analysis | Python (Pandas
• Numpy
• Pyspark
• Scipy
• SQLAlchemy
• Requests
• NLTK
• Matplotlib
• Seaborn
• Plotly)
• Visualization (Tableau
• Matplotlib
• Seaborn
• Plotly
• Power BI
• Visio)
• Machine Learning | Python (Scikit - learn
• Keras pickle
• GridSearchCV
• Random Forest
• Decision Tree
• XGBoost
• Logistic Regression
• SVM
• Naïve Bayes
• KNN
• K Means
• PCA
• RNN
• LSTM
• DNN)
• AWS: S3
• DynamoDB
• Lambda
• Excel (Solver
• Vlookup
• Pivot
• Index/Match)

PROFESSIONAL EXPERIENCE

Confidential, MA

Data Analyst

Responsibilities:

• Translated organizational goals and questions into quantitative analysis.
• Wrote and optimized SQL queries to acquire data, including joins, selection, aggregation, union, case when, window function, etc.
• Extracted data via SQL, Python, Pyspark from various type of data sources like SQL databases, offline, APIs, formats like csv, xls, json, xml.
• Transformed data via SQL and Python for further analysis and modeling, including row operations, joins, sorting, aggregations, cleaning, merging,concatenating, etc.
• Built MySQL-connected applications and pipelines via SQLAIchemy in Jupyter Notebook for extracting data from database, transforming, and doing analysis and visualization.
• Pulled data from an API using Python Requests.
• Implemented data preparation with Python, including data cleansing, handling missing data, Identifying outlier, transforming data.
• Conducted data processing and analysis using Spark SQL; implemented graph analytics and machine learing in Spark.
• Visualized data withMatplotlib, Seaborn, Excel, Tableau, Power BI.
• Built BI dashboards with Tableau, Power BI.
• Facilitated advanced and scalable machine learning models on structured or unstructured data to solve classification, regression, and clustering problems.
• Identified patterns & trends in data; provided insights to enhance business decision making.
• Collaborated with product, science, engineering, and business development teams to develop and deliver data science driven solutions that brought real business value.
• Documented, summarized, and presented findings to a group of peers and stakeholders.
• Figured out optimal configuration for production and supply chain via solving Linear Programming model in order to maximize profit with Excel (Solver).

Confidential

Data Analyst

Responsibilities:

• Wrote fast and reusable SQL to query, extract, and transform data from data sources, gaining required information.
• Wrote HiveQL to query data.
• Developed and maintain dashboards using BI tools such as Tableau, Power BI.
• Explored and analyzed data with tools like Excel to deliver insight, answers and decision support, ending up reporting to stakeholders.
• Visualized data insights and answers with tools of Excel, Tableau, and Python to communicate findings to teams across the organization.
• Forecasted supplies amount via time-series models like moving average, exponential smoothing, saving storage space in warehouse.
• Created WBS(Work Breakdown Structure), Network Diagram with Visio.
• Formulated production planning and shifts planning via Operation Research(Linear programming) with the tool of Excel(Solver).
• Implemented hypothesis testing to confirm if purity of chemical materials were qualified according to confidence interval.
• Managed database of chemical compounds.
• Developed and presented report to tell cohesive and easily-understood stories.
• Transferred data from paper formats into computer files or database system using key borads, data recorders or optical scanners.
• Createdspreedsheets with large numbers of figures without mistakes.
• Sorted and organized paperwork after entering data to ensure it is not lost.
• Retrieved data from Excel or SQL as requested.