Role Proficiency:

Develop data-driven solutions for difficult business challenges. Utilizing analytical statistical and programming skills to collect analyze and interpret large data sets with supervision.
 

Outcomes:

1.       Work with stakeholders throughout the organization to identify opportunities for leveraging data from our customers to create models that can generate business insights
2.       Build predictive models and machine learning algorithms to analyse large amounts of information to discover trends and patterns.
3.       Mine and analyse data from company databases to drive optimization and improvement of product development marketing techniques business strategies etc
4.       Develop processes and tools to monitor and analyse model performance and data accuracy.
5.       Coordinate with different functional teams to implement models and monitor outcomes.
6. Set FAST goals and provide feedback on FAST goals of reportes

Measures of Outcomes:

1.       Number of business processes changed due to vital analysis.
2.       Models applied to Business Problems
3.       Number of Business Intelligent Dashboards developed
4.       Number of productivity standards defined for project
5. Number of mandatory trainings completed
    

Outputs Expected:

Statistical Techniques:

1. Apply statistical techniques for example regression properties of distributions  statistical tests etc. to analyse data.

Machine Learning Techniques:

1. Apply machine learning techniques like clustering decision tree learning artificial neural networks to streamline data analysis etc.

Creating advanced algorithms:

1. Create advanced algorithms and statistics using regression simulation scenario analysis modelling etc.

Data Visualization:

1. Visualize and present data for stakeholders using: Periscope Business Objects D3 ggplot etc.

Management and Strategy:

1. Oversee the activities of analyst personnel and ensures the efficient execution of their duties.

Critical business insights:

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

Code:

1. Create efficient and reusable code meant for the improvement manipulation and analysis of data.

Version Control:

1. Manages project codebase through version control tools e.g. git bitbucket etc.

Prescriptive analytics:

1. Attempts to identify what business course of action to make

Create Reports:

1. Creates reports depicting the trends and behaviours from the analysed data
    
2. Train end users on new reports and dashboards.

Document:

1. Create documentation for personal work as well as performing a peer review of documentation of others' work

Manage knowledge:

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

Status Reporting:

1. Report status of tasks assigned
    
2. Comply with project related reporting standards and process

Skill Examples:

1.       Excellent pattern recognition and predictive modelling skills
2.       Extensive background in data mining and statistical analysis
3.       Expertise in machine learning techniques and creating algorithms.
4.       Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching.
5.       Communication Skills: Communicate effectively with a diverse population at various organization levels with the right level of detail.
6.       Critical Thinking: Data Analysts must look at numbers trends and data and come up with new conclusions based on the findings.
7.       Attention to Detail: Making sure to be vigilant in the analysis to come to correct conclusions.
8.       Mathematical Skills to estimate numerical data.
9.       Work in a team environment
10.   Proactively ask for and offer help
     

Knowledge Examples:

•       Programming languages – Java/ Python/ R / Scala
  1.       Web Services - Redshift S3 Spark DigitalOcean etc.
  2.       Statistical and data mining techniques: GLM/Regression Random Forest Boosting Trees text mining social network analysis etc.
  3.       Google Analytics Site Catalyst Coremetrics Adwords Crimson Hexagon Facebook Insights etc.
  4.       Computing Tools - Map/Reduce Hadoop Hive Spark Gurobi MySQL etc.
  5.       Database languages such as SQL NoSQL
  6.       Analytical tools and languages such as SAS & Mahout.
  7.       Practical experience with ETL data processing etc.
  8.       Proficiency in MATLAB.
  9.   Data visualization software such as Tableau or Qlik.
  10.   Proficient in mathematics and calculations.
  11.   Utilization of spreadsheet tools such as Microsoft Excel or Google Sheets
  12.   DBMS
  13.   Operating Systems and software platforms
  14.   Knowledge regarding customer domain and sub domain where problem is solved
  15.   Proficient in at least one version control tool like git bitbucket
  16. Have experience working with project management tool akin to Jira