Associate Data Scientist Ii

Role Proficiency:
Independently develop data-driven solutions to difficult business challenges by utilize analytical statistical and programming skills to collect analyze and interpret large data sets under supervision.

Outcomes:

- Work with stakeholders throughout the organization to identify opportunities for leveraging data from our customers to make models that can generate business insights
- Create new experimental frameworks or build automated tools to collect data
- Correlate similar data sets to find actionable results
- Build predictive models and machine learning algorithms to analyse large amounts of information to discover trends and patterns.
- Mine and analyse data from company databases to drive optimization and improvement of product development marketing techniques business strategies etc
- Develop processes and tools to monitor and analyse model performance and data accuracy.
- Develop Data Visualization and illustrations on given business problem
- Use predictive modelling to increase and optimize customer experiences and other business outcomes.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Set FAST goals and provide feedback on FAST goals of reportees

Measures of Outcomes:

- Number of business processes changed due to vital analysis.
- Number of Business Intelligent Dashboards developed
- Number of productivity standards defined for project
- Number of Prediction and Modelling models used
- Number of new approaches applied to understand the business trends
- Quality of data visualization done to help non-technical stakeholders comprehend easily.
- Number of mandatory trainings completed

Outputs Expected:
Statistical Techniques:
properties of distributions
statistical tests
etc. to analyse data.

Machine Learning Techniques:
decision tree learning
artificial neural networks
etc. to streamline data analysis.

Creating advanced algorithms:

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

Data Visualization:

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

Management and Strategy:

- Oversees the activities of analyst personnel and ensures the efficient execution of their duties.

Critical business insights:

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

Code:

- Creating efficient and reusable code meant for the improvement
manipulation
and analysis of data.

Version Control:

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

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

Create Reports:

- Creates reports depicting the trends and behaviours from the analysed data
- Training end users on new reports and dashboards.

Document:

- Create documentation for own work as well as perform peer review 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 process

Skill Examples:

- Excellent pattern recognition and predictive modelling skills
- Extensive background in data mining and statistical analysis
- Expertise in machine learning techniques and creating algorithms.
- 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 look at numbers trends and data and come to new conclusions based on the findings.
- Strong meeting facilitation skills as well as presentation skills.
- Attention to Detail: Making sure to be vigilant in the analysis to come to correct conclusions.
- Mathematical Skills to estimate numerical data.
- Work in a team environment and have strong interpersonal skills to work in collaborative environment
- Proactively ask for and offer help

Knowledge Examples:

- Programming languages - Java/ Python/ R.
- Web Services - Redshift S3 Spark DigitalOcean etc.
- Statistical and data mining techniques: GLM/Regression Random Forest Boosting Trees text mining social network analysis etc.
- Google Analytics Site Catalyst Coremetrics Adwords Crimson Hexagon Facebook Insights etc.
- Computing Tools - Map/Reduce Hadoop Hive Spark Gurobi MySQL etc.
- Database languages such as SQL NoSQL
- Analytical tools and languages such as SAS & Mahout.
- Practical experience with ETL data processing etc.
- Proficiency in MATLAB.
- Data visualization software such as Tableau or Qlik.
- Proficient in mathematics and calculations.
- Spreadsheet tools such as Microsoft E