Using knowledge of advanced analytics, data mining and statistical techniques, the Principal Data Scientist designs and develops enterprise analytic solutions for Jabil’s customers to improve business performance. This role defines best practices in the use of advanced analytics and influences process improvement.
The Principal Data Scientist researches emerging technologies to evaluate new analytic possibilities. This position designs and develops prototypes & proof-of-concept solutions in support of presales activities, as well as, supports the development of standardized analytic offerings across multiple business functions.
ESSENTIAL DUTIES AND RESPONSIBILITIES
· Provides analytic strategies to meet demands of business requirements.
· Offers technical and data requirements of the analytic solutions.
· Conducts sophisticated data mining analyses and build data mining models, as required, as part of the initial solution development.
· Translates data mining results into clear business focused deliverables for decision makers.
· Supports Application Developers to deploy data mining models into operational systems.
· Provides best practices for applying data mining to problem domain.
· Designs and/or contributes to the development of a data mining systems that enable reuse, efficiency, manageability and deployment.
· Integrates advanced analytics into end-to-end business intelligence solutions and operational business processes.
· Verifies and implements the detailed technical design solution to the problem as identified by the Project/Technical Manager.
· May act as the Principal Consultant who analyzes and develops enterprise technology solutions.
· Often leads the technical assessment and delivery of specific technical solutions to the customer.
· Provides advanced technical consulting and advice on proposal efforts, solution design, system management, tuning and modification of solutions.
· May provide input to the business strategy moving forward.
· Collects and determines data from appropriate sources to assess customer needs and requirements. Responds to requests for technical information from customers. Develops customer technology solutions using various industry products and technologies.
· Engages in technical problem solving across multiple technologies; often needs to develop new methods to apply to the situation.
· Owns and manages knowledge sharing within a community (e.g. team, practice, or project).
· Ensures team members support knowledge sharing and re-use requirements of project. Contributes significant knowledge to job family community.
· Proactively encourages membership and contributions of others to professional community and coaches others in area of expertise.
· Regularly produces internally published material such as knowledge briefs, service delivery kit components and modules, etc. Presents at technology conferences.
· May perform other duties and responsibilities as assigned.
· Expert use of data mining methodologies such as classical regression, logistic regression, CHAID (Chi-squared Automatic Interaction Detection), CART (Classification and Regression Trees), neural nets, association rules, sequence analysis, cluster analysis, and text mining.
· Expert use of SQL and experience with relational databases
· Experience with Hadoop, Map/Reduce, Hive or equivalent
· Ability to manage multiple projects efficiently and able to meet deadlines
· Excellent communication and presentation skills; fluent in English.
· Has sufficient depth and breadth of technical knowledge to design and scope multiple deliverables across a number of technologies.
· Has demonstrated innovation and communication of new deliverables and offerings. Has led team in the delivery of multiple deliverables across multiple technologies.
· Ability to develop solutions that enhance the availability, performance, maintainability and agility of the enterprise.
· Has contributed to the design and application of new tools. Ability to re-use existing experience to develop new solutions to take to market.
· Ability to drive a team structure conducive to high performance, and manages the team lifecycle stages.
· Possesses an understanding, at a detailed level, of architectural dependencies of technologies in use in the analytic environment.
· Frequently uses product and application knowledge along with internals or architectural knowledge to develop solutions.
· A recognized expert in one or more technologies within own technical community and also at regional level. Holds a vendor or industry certification in at least one discipline area.
· Able to communicate with internal and external senior management confidently and demonstrate the professionalism of the job family.
· Ability to work in a multi technology environment with the ability to diagnose complex technical problems to their root cause. In addition to troubleshooting skills and consulting skills, has ability to summaries prognosis and impact at practice lead level.
· Familiarity with Hadoop, APS, Data Security, MDM, SaaS, “R” and related helpful hands on & Strategic
· Ability to adapt a consulting style appropriate to the situation and can identify up-sell opportunities.
· Be able to demonstrate a broad understanding of market dynamics, an industry area, commercial issues, and technical concerns whilst maintaining depth in core focus area.
· Ability to present within own area of expertise as part of a customer presentation, putting forward domain specific information within the context of a sales campaign.
· Has demonstrated ability to lead others in the gathering of requirements, designs, plans and estimates.
· Able to produce complete proposals for smaller engagements within own area of expertise.
· Demonstrates broad knowledge in other technical areas in order to properly manage complex integration efforts.
· Demonstrates application of technical expertise in successful engagements involving multiple disciplines.
· Able to independently complete solution implementation or application design deliverables.
- Image recognition and object detection;
- Convolution Neural Network and deep learning with Tensorflow, Keras as well as Pytorch;
- Machine learning Operations and Engineering;
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