Teradata TB Prin. Data Scientist (I) in North Sydney, Australia
TB Prin. Data Scientist (I)
The Data Scientist gathers intelligence from the massive streams of data that clients gather each day. Due to the volume of data, its multi-structured nature, and the various advanced analysis involved, MapReduce and other advanced software available with, for example, Teradata Aster and Hadoop are used to supplement or in place of traditional SQL analysis. Data can originate anywhere; from sales records, web logs, and web crawlers to jet engines, electronic switches, and countless other sources. The Data Scientist sifts through the data for useful nuggets of information, and then presents results to the client to allow business decisions to be made on the findings. The Data Scientist captures, sorts, and determines what is relevant in the data.
The analysis process involves assembling and preparing the data, writing the software programs, and executing the actual analysis. Advanced analysis is required on the data that includes data mining and statistical analysis. A background in computer science or a related technical field such as math or physics is required. Computer science programming expertise is desirable to analyze the data and provide intelligence that leads to better business decisions or new products. The Data Scientist will also have a strong analytic background, typically in mathematics and the application of statistics. Techniques are used to detect patterns in large volumes of data for applications such as forecasting, response modeling, fraud detection, and segmentation. Industry specific methods and solutions are used to solve industry specific tasks. Strong communication skills are required to convey complex analytical results to business sponsors of programs. The Data Scientist provides solutions in the cloud, on premises, and in mixed environments. The Data Scientist may be the Project Tech Lead on a project.
Key Areas of Responsibility
Clarify the business problem for the purpose of data analysis.
Translate the business requirements into technical requirements.
Translate the requirements into existing advanced analytic functions or help design new functions with MapReduce or other 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. Teradata’s 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. At the conclusion of 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 Hadoop and MapReduce (Teradata Aster, Hive, Pig, etc.).
Explore – base skills in statistics, algorithms, machine learning, and mathematics. A solid grounding in these principles is required to actually 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
Primary Location: Asia Pacific/Japan-Australia-New South Wales-North Sydney
Organization: TB International
Req ID: 174115