Key Areas of Responsibility
Clarify the business problem for data analysis.
Translate the business requirements into technical requirements.
Translate the requirements into existing advanced analytic functions or help design new functions with software to meet the requirements.
Work closely with the client teams to generate insights, diagnose problems, and provide information for business and product decisions by transforming very large data sets into actionable information.
Build and maintain tools and documentation to enable the consumption of data by the platform team and the entire company.
Perform both regular and ad-hoc analysis leveraging a wide array of data tools.
Interpret and document the analysis and results, and communicate the information effectively to the client.
All consultants are expected to build value in themselves. Teradatas extensive library of both instructor led and web based training provides ample opportunity for the consultant to build and maintain marketable skills.
Time has been allocated specifically for this task and each consultant is expected to have a Learning Plan. Progress against the learning plan is part of the annual appraisal.
All consultants are expected to build value in their practice through the contribution and reuse of consulting assets.
After each assigned project, a consultant is expected to evaluate the project deliverables and to contribute those items that may be useful to other consultants that may be assigned similar projects.
When a new project is assigned, the consultant will search the asset repository for assets that may improve or accelerate the project delivery.
Experience with large data sets and distributed computing with Teradata, Hadoop and MapReduce (Hive, Pig, etc.).
Explore base skills in statistics, algorithms, machine learning, and mathematics. A solid grounding in these principles is required to extract signals from the data and build things with it.
Build experienced with at least one programming language, preferably Java. While advanced coding techniques are not required, the candidate needs to be aware of the open source libraries and packages available.
Communicate making the results real by making data available to users. This involves communicating the results of analysis clearly and effectively to both business and technical users in presentations.
Lead the discussion and guide the integration of the data visualization layer with the underlying platform to best showcase the output of the data.
In depth knowledge of statistics and mathematics.
Computer Science or related mathematics background to have the math and statistics knowledge required for data science.
In depth knowledge of analytical toolsets.
Experience building software is a plus.
Fluency in SQL
Knowledge across multiple industries is a plus.
Ability to initiate and drive projects to completion with minimal guidance
Knowledge of Architecture Principles, Advocated Positions, Design Patterns, and Implementation Alternatives.
Understanding of the Teradata Reference Information Architecture.
Work with the appropriate project management methodology (Agile or Waterfall) based upon customer and project requirements
Project Mgmt : Data Warehousing Skills
Tools Business Intelligence
Tools Enterprise Application Integration