Technical SE Specialist - Data Analytics
Plano, TX, United States
Job Description Summary
JOB PROFILE SUMMARY: Leverages data science concepts to solve problems and provide solutions. Establishes the pre-sales support strategy basis for current and prospective clients. Works with vendors, partners, and sales to ensure that optimum systems solutions are provided to new and existing customers. Develops processes and systems to provide quick yet thorough responses to customer Requests For Proposal. Provides pre-sales support and systems configuration recommendations. Develops and applies methods, theories, and research techniques to provide solutions to technical problems. Plans, conducts, and directs projects including costs, staffing, technical leadership, and project evaluation. Serves as a technical resource for long-range planning.
INDEPENDENCE: Proactive self-starter capable of working independently and collaboratively. Provides regular updates to the manager on project/account status.
SKILLS/EXPERIENCE: Strong competence with the various tools, procedures, and programming/querying languages used in Data Science and Data Engineering.
Job Description
Ribbon is looking for a Technical SE Specialist to support the Americas Service Provider and Federal Government account bases. This is a Pre-Sales Systems Engineering role where the primary responsibility is to assist account teams in closing new business. The 'Technical SE Specialist - Data Analytics' role is focused on providing solutions for our Ribbon Analytics platform which is based on tool sets common in data science. The Technical SE Specialist will use data science concepts to tackle complex problems and must be well versed with concepts such as EDA, Data Preprocessing, Feature Engineering and Model Training. The Technical SE Specialist will provide technical assistance to various sales teams and will have responsibility for demos, trials, and proof of concept activity across the region. The Technical SE Specialist will liaison with both the account as well as the associated account team to drive these activities to completion.
Responsibilities
Act as a subject matter expert on data science and Ribbon Analytics for the account teams
Help identify, through customer interactions, the key use cases and data sets required to extract meaningful intelligence that helps the customer address a need
Work with the engineering and other pre-sales PoC assets to model and present a compelling value-add to the customer that ensures a purchase
Provide competitive intelligence back to PLM / R&D teams on capability, pricing, and offers that are being seen with customers and potential customers
Coordinate, lead, and perform lab/POC trials, and where required design the installation of trial equipment
Understand and be proficient with the use of Ribbon equipment in a Ribbon lab environment. Lead demonstrations on Ribbon Analytics capabilities in that environment for customers where such demonstrations may advance sales efforts or lead to purchase decisions
Provide technical support to the various account teams to ensure that the best and most appropriate Ribbon solution is selected
Interface with Ribbon Product development to review and plan for customer requirements
Interface with customers and Ribbon engineering as issues arise, monitor bug fixes, and track feature development in code releases and help ensure that the relationship between Ribbon and the account is strong
Provide technical support in sales presentations and product demonstrations. This includes assisting Pre- and Post-sales efforts within the account
Provide answers to customer enquiries concerning system software and applications
Become the Trusted Advisor within target accounts, offering expert guidance on Ribbon solutions
Skills & Experience
Strong knowledge of data analytics, manipulation of data sources, and data visualization skills to communicate actionable information
Strong understanding of the difference between data and actionable data
Use of statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for diagnosis and prediction
Strong mathematical skills to help collect, measure, organize and analyze data
Knowledge of how to create and apply the most accurate data science algorithms relevant to the problem and find solutions
Proven experience with data science methodologies and tools common in the industry including Pandas, Numpy, and Scipy
Familiarity with data visualization tools like Grafana, Zoomdata, Seaborn, Matplotlib
Knowledge of data querying and programming languages like SQL and Python
Knowledge of Hadoop or other non-SQL 'big-data' data lake database technology
Background including data collection, correlation, bucketization, and analysis
Knowledge of Kubernetes, Linux, and basic IP Networking
Familiarity with NFV, OpenStack and Containers is highly desirable as well as a strong understanding of Cloud environments (AWS, Azure, Google)
Telecom domain knowledge in VoIP, IMS, LTE, and 5G preferable but not required
Bachelor's degree in engineering, computer science or related technical areas of study
3-5 years of working in an Analytics technical field or additional advanced education
Self-starter with excellent communication, presentation, and writing skills
Flexible to juggling schedules and travel tolerant
Hands-on skills with installing, running, and troubleshooting trials and demos
Pro-active approach to driving technical engagements, ensuring that any issues are escalated and managed to successful conclusion
Excellent team player looking to make a real impact with strong communication (verbal and written), presentation and interpersonal skills
Excellent spoken and written English
Please Note:
'All qualified applicants will receive consideration for employment without regard to race, age, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, on the basis of disability, or other characteristic protected by applicable law.'
US Citizens and all other parties authorized to work in the US are encouraged to apply.
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