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Data Analyst/lecturer Resume

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Iowa City, IA

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SUMMARY:

  • 8 years of experience providing advanced analytical solutions to support business processes; expert skills in translating complex business needs into clear analytical requirements and providing customized strategic solutions; certified in business process and system integration; strong knowledge of SQL (packages, functions, stored procedures, triggers, etc.), physical/logical database design/development as well as
  • ETL data integration, and Python (Pandas and scikit - learn, etc.); strong knowledge of database object modeling and performance optimization; strong communication, report writing and presentation skills; critical thinker; active solution provider; detail-oriented; proficient in project management.

TECHNICAL SKILLS:

SKILLS: SQL, MySQL, SQL Server, PL/SQL, Oracle, Postgres, Python, Java, XML, HTML, JSON, SAS, JMP, SPSS, Hadoop (MapReduce+HDFS), Tableau, PowerBI (connecting to various SaaS solutions to load dynamic data from cloud sources and build reports and dashboards), Google Analytics/Data Studio, QlikView, Microstrategy, Salesforce, Rapid Insight, Mixpanel, MS Excel VBA, MS Access, MS Visual Studio, MS Visio, MS Office, SAP, PeoleSoft, Crystal Reports, Adobe Creative Cloud, SharePoint, Citrix, Trello.

PROFESSIONAL EXPERIENCE:

Data Analyst/Lecturer

Confidential, Iowa City, IA

Responsibilities:

  • Conducted in-depth functional and non-functional requirements gathering from internal/external users and prepared detailed documentations such as business requirements, functional requirements and functional specifications.
  • Managed the entire life-cycle of the projects overseeing multiple priorities and coordinated collaborations across functional departments, technical teams and leadership to identify processes/data/system/hardware/software improvement opportunity based on data.
  • Created system improvement plans (including problem definitions, business questions, use scenario descriptions, process task checklists, process inventories, workflow process diagrams, role-based flowcharts, ERDs, database system/application designs, goals and objectives for the designs, business processes supported, high-level functional requirements, information architecture, summary of changes, test cases, etc.) and implementing plans (including user experience reflections, quality improvement models, measure-change-learn cycles, implementation recommendations, error reporting, change management, data quality improvements, vendor surveys, etc.).
  • Supported users throughout deployment and maintained the solutions. Communicated vigorously with various executive stakeholders as well as created multimedia user guides, hosted s and supported non-technical users throughout solution adoption and customization to maximize success.
  • Scalable data management:
  • Managed and owned large, complex sets of dynamic data (structured and unstructured) from large SQL databases and guarded data integrity/quality/security.
  • Extracted internal/external data, transformed and loaded into data warehouses across platforms using ETL tools.
  • Prepared and validated data, performed ad-hoc analysis and created reports using query/programming. Optimized SQL, PL/SQL code for performance tuning.
  • Joined “islands of data” across enterprise (from various processes such as accounting, records management, advancement, services, etc.) together for cohesive business understanding and centralized strategic deep dives.
  • Built a highly scalable data warehouse with HBase on top of Hadoop including the ETL migration processes and implemented Hive and MapReduce processing jobs using Python.
  • Customers/user and product:
  • Won UIOWA innovation for a mobile product solution in maximizing user benefits.
  • Built business growth strategies based on customer health analysis and churn risks of accounts predictions such as to differentiate customer outreach efforts based on quantified customer health score.
  • Utilized web analytics to keep track of all the customer engagement touchpoints and generated large scale trends and patterns in customer lifecycle behavior.
  • Used customer demographic and behavioral data to reveal user grouping descriptors by applying a variety of segmentations and comparing the cluster means such as the characteristics of the high-value customers.
  • Used domain-specific unstructured data generated online or in customer relationship management (such as textual documents, XML files, emails, web pages, short notes, and voice recordings) from help centers, user feedback, live support, social media, etc. with qualitative/quantitative models to assess user experience, generated issues and measure support channels’ impacts on customer success.
  • Conducted extensive experiments such as A/B testing and Cohort analysis on user acceptance to bring insightful solutions for optimization before new product commercialization.
  • Evaluated product performance and market sustainability throughout product lifecycle to formulate progressive product overall strategies and worked with a cross-functional agile team to automate the data collecting and reporting.

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