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Data Analyst Resume

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MA

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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.

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