Lead I - Data Science

Role Proficiency

Provide expertise on data analysis techniques using software tools. Under supervision streamline business processes.

Outcomes

 

• Design and manage the reporting environment; which include data sources security and metadata.
• Provide technical expertise on data storage structures data mining and data cleansing.
• Support the data warehouse in identifying and revising reporting requirements.
• Support initiatives for data integrity and normalization.
• Assess tests and implement new or upgraded software. Assist with strategic decisions on new systems. Generate reports from single or multiple systems.
• Troubleshoot the reporting database environment and associated reports.
• Identify and recommend new ways to streamline business processes
• Illustrate data graphically and translate complex findings into written text.
• Locate results to help clients make better decisions. Solicit feedback from clients and build solutions based on feedback.
• Train end users on new reports and dashboards.
• Set FAST goals and provide feedback on FAST goals of repartees
  
   

Measures Of Outcomes

 

• Quality - number of review comments on codes written
• Data consistency and data quality.
• Number of medium to large custom application data models designed and implemented
• Illustrates data graphically; translates complex findings into written text.
• Number of results located to help clients make informed decisions.
• Number of business processes changed due to vital analysis.
• Number of Business Intelligent Dashboards developed
• Number of productivity standards defined for project
• Number of mandatory trainings completed
  
   

Outputs Expected

Determine Specific Data needs:

 

• Work with departmental managers to outline the specific data needs for each business method analysis project
  
   

Critical Business Insights

 

• Mines the business’s database in search of critical business insights; communicates findings to relevant departments.
  
   

Code

 

• Creates efficient and reusable SQL code meant for the improvement manipulation and analysis of data.
• Creates efficient and reusable code. Follows coding best practices.
  
   

Create/Validate Data Models

 

• Builds statistical models; diagnoses validates and improves the performance of these models over time.
  
   

Predictive Analytics

 

• Seeks to determine likely outcomes by detecting tendencies in descriptive and diagnostic analysis
  
   

Prescriptive Analytics

 

• Attempts to identify what business action to take
  
   

Code Versioning

 

• Organize and manage the changes and revisions to code. Use a version control tool for example git bitbucket. etc.
  
   

Create Reports

 

• Create reports depicting the trends and behaviours from analyzed data
  
   

Document

 

• Create documentation for worked performed. Additionally perform peer reviews of documentation of others' work
  
   

Manage Knowledge

 

• Consume and contribute to project related documents share point libraries and client universities
  
   

Status Reporting

 

• Report status of tasks assigned
• Comply with project related reporting standards and processes
  
   

Skill Examples

 

• Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.
• Communication Skills: Communicate effectively with a diverse population at various organization levels with the right level of detail.
• Critical Thinking: Data Analysts must review numbers trends and data to come up with original conclusions based on the findings.
• Presentation Skills - facilitates reports and oral presentations to senior colleagues
• Strong meeting facilitation skills as well as presentation skills.
• Attention to Detail: Vigilant in the analysis to determine accurate conclusions.
• Mathematical Skills to estimate numerical data.
• Work in a team environment
• Proactively ask for and offer help
  
   

Knowledge Examples 

 

• Database languages such as SQL
  • Programming language such as R or Python
  • Analytical tools and languages such as SAS & Mahout.
  • Proficiency in MATLAB.
  • Data visualization software such as Tableau or Qlik.
  • Proficient in mathematics and calculations.
  • Efficiently with spreadsheet tools such as Microsoft Excel or Google Sheets
  • DBMS
  • Operating Systems and software platforms
  • Knowledge regarding customer domain and sub domain where problem is solved

Desired Skills and Experience

Python,Data Modeling,Metadata Management,Sql