Associate Data Scientist
Description:
Not Applicable
Qualification:
Post-grad in one of the following fields with strong academic credentials:
• Computer Science/IT.
• Operations Research/Applied Math.
• Engineering.
• Statistics.
Responsibility:
Business:
'Works with the business team to identify the right business objective and data required to answer the same.
Executes a data collection plan from both structured and unstructured sources that helps in data exploration, hypothesis testing and statistical modeling.
Analyzes data and generates insights that can articulated to business stakeholders.
Develops POCs that can be used to generate business decisions.
Simulates several scenarios through an interactive visualization that deepens the business understanding with underlying trends and root causes.
Stakeholder Management:
'• Communicate analytical results in a way that is meaningful for business stakeholders and provides actionable insights.
• Coordinates in communicating the data needs with both technology and business teams to ensure that right data is captured for analysis and modeling.
Project Management:
'• Ensure that the work goes ahead in a way that conforms to DS delivery framewrok and fulfills all outputs specifically outlined by stakeholders.
• Work with Business Operations and Delivering teams on designing, building and deploying data analysis systems for large data sets.
• Execute flawlessly on the DS project plan by adhering to timelines.
• Execute the design, analysis, or evaluation of assigned projects.
Data Analytics and Reporting:
'• Explore and examine data from multiple disparate sources.
Prepare a data collection plan from both structured and unstructured sources.
Collaborate and coordinate with Technology and Business teams for all data needs.
• Expert level proficiency in data handling (SQL).
Data Discovery & Profiling.
Data Discovery & Profiling:
'• Perform exploratory data analysis and generate insights.
Validate hypothesis developed during exploration phase.
Present initial results to business stakeholders and identify the next steps.
Data Modelling:
Create models using one or more of the platforms like R, SAS, Python, Matlab Model creation would involve one or more of the following technqiues:
1 Classification.
2 Clusterning.
3 Time Series.
4 Forecasting.
'• Testing and validating the model.
• Deriving insights and recommendations from the models.
• Performing data visualization and presentation to clients.
Innovation & Thought Leadership:
'• Provide thoughtleadership and dependable execution on diverse projects.
• implement best practices and technology.
• Discover new opportunities where advanced analytical techniques can be leveraged for solving business problems.
Knowledge Management:
Document all modeling steps in a systematic way including modeling process, insights generated, presentations, model validation results and checklists built in the project.
Prepare a one pager document that outlines and quantifies the business impact due to the DS project.
Must Have Skills
BigQuery
SQL Developer
Item Management
Technical Skills
SNo Primary Skill Proficiency Level * Rqrd./Dsrd.
1 BigQuery PL1 Required
2 SQL Developer PL1 Required
Domain Skills
SNo Primary Skill Proficiency Level * Rqrd./Dsrd.
1 Item Management NA Required
* Proficiency Legends
Proficiency Level Generic Reference
PL1 The associate has basic awareness and comprehension of the skill and is in the process of acquiring this skill through various channels.
PL2 The associate possesses working knowledge of the skill, and can actively and independently apply this skill in engagements and projects.
PL3 The associate has comprehensive, in-depth and specialized knowledge of the skill. She / he has extensively demonstrated successful application of the skill in engagements or projects.
PL4 The associate can function as a subject matter expert for this skill. The associate is capable of analyzing, evaluating and synthesizing solutions using the skill.
Schedule: Full-time
Shift: Day Job
Travel: No