Full-Time

Customer Success Lead Data Scientist

High Tech Manufacturing

Posted on 9/23/2025

Deadline 9/26/25
TIBCO Software

TIBCO Software

1,001-5,000 employees

Real-time data integration & analytics platform

Compensation Overview

$179.6k - $269.4k/yr

+ Annual Bonus + Sales Incentives

California, USA + 1 more

More locations: Texas, USA

In Person

The candidate needs to be in California or Texas.

Category
Sales & Account Management
Data & Analytics (1)
Required Skills
LLM
Microsoft Azure
Python
Data Science
R
SQL
Machine Learning
QlikView
Tableau
AWS
Data Analysis
Requirements
  • 5+ years of experience in applying analytics to the High Tech Manufacturing sector problems.
  • 5+ years of experience in advanced data analytics and delivery of demonstrations, projects, engagements or deployed software applications. Experience with applying advanced analytics such as machine learning and optimization techniques to large, complex and disparate data sources.
  • Superior communication and storytelling skills with data. The ability to comfortably communicate with customers’ senior industry personnel, provide compelling presentations and demonstrations of analytics software, and the business value of analytics projects demonstrating domain knowledge in a key Industry such as Manufacturing, Energy, Telecommunications, Financial Services, Healthcare, or Retail.
  • Capability to formulate a real-world problem into a mathematical equivalent, propose various solutions, compare and contrast them, deploy the solution, validate the results, and present the results to technical and non-technical stakeholders.
  • 5+ years of experience with Python or R and some knowledge of SQL. Some experience with other software environments e.g. Spotfire, Tableau, Qlikview, SPSS, KNIME, Azure, AWS and/or other data mining tools will be a plus.
  • Excellent communication and collaboration skills, with the ability to work effectively in a team environment and communicate technical concepts to non-technical stakeholders
  • Strong problem-solving skills, with the ability to identify key areas for improvement and develop data-driven solutions to address them.
  • A Master’s or higher degree in STEM (Computer Science, Statistics, Data Science, Engineering, Science, or related analytical field of study) with graduate classes in statistics and data mining.
Responsibilities
  • Lead technical customer engagements through understanding Spotfire use cases, providing guidance, and building prototypes. The High Tech Manufacturing sector will be the primary focus.
  • Collaborate closely with other customer account team members to ensure customer success
  • Collaborate with stakeholders on specific industry knowledge, analytics use cases and customer stories related to data science or machine learning in the High Tech Manufacturing sector
  • Delve deep into manufacturing, energy, or similar types of analytical and data science challenges.
  • Engage with customers through presales support and post-sales success projects.
  • Perform and guide R&D topics in the field of applied machine learning and AI.
  • Example topics of research and projects include Large Language Models, digital twin, anomaly detection in time series, or mathematical modeling of manufacturing processes.
  • Create re­usable data models, workflows and test suites in order to streamline project delivery.
  • Provide input into product management and engineering for the product roadmap.
  • Innovate in the areas of application and deployment of machine learning.
  • Tool Kit Development: create demos and templates with data science libraries.
  • Technical marketing: create white papers, blogs and content for the Spotfire user community.
  • Represent the team as a speaker or instructor in industry events and external conferences.
Desired Qualifications
  • Experience with other software components for data preparation and integration e.g. Data Virtualization and Big Data tools such as Hadoop and Spark and/or further programming or scripting environments e.g. .Net, Java, IronPython, Javascript, C++ is a plus.
  • A PhD in STEM (Computer Science, Statistics, Data Science, Engineering, Science, or related analytical field of study) with graduate classes in statistics and data mining.

TIBCO Software provides a platform for real-time data integration and analytics that helps businesses connect, unify, and analyze data to improve decision-making and operational efficiency. Its tools are used by healthcare providers, financial institutions, and large enterprises. The company earns money from software licensing, subscriptions, and professional services, and its platform can be deployed on-premises, in the cloud, or in hybrid environments. It emphasizes high performance, reliability, and scalability for mission-critical applications. Unlike many competitors, TIBCO combines comprehensive data integration with analytics across flexible deployment models, serving large organizations that need real-time data flows. The goal is to help organizations manage their data more effectively to support faster, better decisions and smoother operations.

Company Size

1,001-5,000

Company Stage

Acquired

Total Funding

$4.3B

Headquarters

Palo Alto, California

Founded

1997

Simplify Jobs

Simplify's Take

What believers are saying

  • TIBCO Cloud Integration launches in AWS Marketplace, expanding enterprise reach.
  • Flogo MCP reduces MTTR by 35% for P1 incidents via AI root-cause analysis.
  • Model Context Protocol enhances SRE workflows with structured data logging.

What critics are saying

  • Cloud Software Group lays off 1,000 TIBCO employees in September merger.
  • CSG CEO Tom Krause cuts mid-tier clients, losing to MuleSoft competitors.
  • Databricks Lakehouse captures Spotfire's real-time analytics market share.

What makes TIBCO Software unique

  • TIBCO Flogo 2.26.0 introduces MCP Connector for AI-driven incident response.
  • Smart Incident Response Assistant automates triage with PagerDuty integration.
  • Hyperconverged Analytics in Spotfire enables action triggering from insights.

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Benefits

Health Insurance

Life Insurance

Disability Insurance

401(k) Retirement Plan

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
TIBCO
Apr 2nd, 2026
How to automate Smart Incident Response with TIBCO Flogo(R) and Model Context Protocol(MCP).

How to automate Smart Incident Response with TIBCO Flogo(R) and Model Context Protocol(MCP). April 2, 2026 TIBCO Flogo(R) automates incident response by combining Model Context Protocol (MCP) tools for interactive data collection, real-time logging, and AI-driven root-cause analysis. Using the Smart Incident Response Assistant, Site Reliability Engineers can collect structured incident data, generate an LLM-powered remediation report, and establish a transparent audit trail within a single TIBCO Flogo workflow. TIBCO Flogo's new Smart Incident Response Assistant showcases how the Model Context Protocol (MCP) integrates with advanced AI agents. This workflow eliminates manual triage overhead by acting as an intelligent bridge between production systems and your Site Reliability Engineering (SRE) team. For a foundational look at these capabilities, see its full guide on TIBCO Flogo(R) Model Context Protocol(MCP) Showcase Sample - Smart Incident Response Assistant. How does the TIBCO Flogo Incident Response architecture work? * Initial Trigger: An engineer prompts the AI with a symptom like "Payment system down". * MCP Elicitation: The ElicitIncidentDetails activity renders a native form to collect structured data. * Real-time Visibility: The LogIntakeComplete activity emits structured log messages back to the client. * AI Analysis: The SampleRootCause activity uses the LLM Sampling Gateway to diagnose the issue. * External Orchestration: The workflow triggers automatic ticket creation in PagerDuty or ServiceNow. Automating Incident Response triage with the TIBCO Flogo MCP Connector. The assistant implements three key capabilities within a single workflow to ensure high "Information Gain" and machine readability: * MCP Elicitation: Interactive intake forms via the ElicitIncidentDetails activity collect affected system and severity data. * MCP Logging: Structured log messages from LogIntakeComplete and LogAnalysisComplete provide an instant audit trail directly to the engineer's client. * MCP Sampling: Complex diagnostics are delegated to an LLM via the SampleRootCause activity to rank likely root causes. Why is ai-driven root-cause analysis critical for SRE teams? Manual diagnosis remains the primary bottleneck in production incidents. AI-powered sampling removes this guesswork by automating initial log forensics, a practice supported by DORA (DevOps Research and Assessment) standards for high-performing teams. Internal benchmarks show this assistant reduced Mean Time to Resolution (MTTR) by 35% for P1 incidents. "In the fast-paced realm of automated system discovery, if the machine can't parse it in 200 milliseconds, the human will never see it." Frequently asked questions. How does TIBCO Flogo automatically create tickets? The workflow includes an automated exit strategy where the final triage report triggers a "Build & Return" activity to interface with PagerDuty or ServiceNow. What is the role of LLM Sampling? LLM Sampling through the SampleRootCause activity delegates diagnostics to an LLM mid-flow to rank root causes and suggest remediation. What are the prerequisites for the Flogo MCP Connector? Flogo MCP connector is available in Flogo 2.26.0 release onwards. You can download it from here. Key takeaways. * Automated Intake: TIBCO Flogo uses MCP Elicitation for structured reports. * Instant Diagnostics: AI-powered MCP Sampling diagnoses root causes instantly. * Zero-Lag Compliance: MCP Logging provides a transparent audit trail. Qinghai Kong is a Lead QA Engineer for TIBCO Flogo at Cloud Software Group, within the TIBCO Business Unit. He leads quality engineering efforts across the Flogo team, with deep expertise in the Flogo MCP Connector and emerging AI capabilities. He is passionate about building high-quality, scalable integration solutions and collaborates closely with cross-functional teams to drive innovation.

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