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Customer Success Manager - Data- Missionforce - TS​/SCI Clearance

Job in McLean, Fairfax County, Virginia, USA
Listing for: Salesforce
Full Time position
Listed on 2026-05-18
Job specializations:
  • IT/Tech
    Technical Support, Data Science Manager
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Customer Success Manager - Data360 - Mission force - TS/SCI Clearance

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Role Description

The Customer Success Manager (CSM) is a versatile expert responsible for ensuring high‑value customers who purchase the Signature Success Plan achieve a significant return on their investment with our platform. As an extension of the customer’s workforce, the CSM is a trusted advisor who identifies and addresses both technical and business concerns, aligning them strategically with customer priorities, projects, and problems.

Industry

Experience
  • National Security (Nat Sec) – Serve defense, intelligence, and law enforcement agencies and implement secure cloud solutions that meet stringent government security standards.
Responsibilities
  • Serve as the single point of customer accountability responsible for the delivery of all Signature deliverables, the overall customer experience, and renewal and expansion.
  • Coordinate all deliverables the customer is entitled to, overseeing the experience throughout the Signature lifecycle.
  • Apply the correct processes to address customer needs and ensure value is delivered through the Signature offer.
  • Successfully align with and manage both Business and Technical Stakeholders, focusing on aligning Business Value and Technical Goals to the Signature offer.
  • Prioritize the most urgent work activities, organize tasks to avoid missing key steps, and create basic plans to focus time.
  • Use internal resources to increase effectiveness and rely on managers or mentors for guidance on priority problems.
  • Conduct enablement sessions on opportunity and case management, forecasting, pipeline hygiene, knowledge creation, and omni‑channel routing.
  • Share best practices for sales and service process optimization, data quality, and customer experience.
  • Drive adoption of Sales and Service Cloud features with reps, agents, managers, supervisors, and ops teams.
  • Track usage metrics such as opportunity updates, activity logging, forecast submissions, report usage, case resolution times, knowledge article usage, channel adoption, and CSAT scores.
  • Develop and maintain strong relationships at key stakeholder levels, including cultivating executive‑level relationships within customer IT and business leadership.
  • Act as a trusted advisor by gaining trust through mutual goals and applying proven solutions to customers’ problems.
  • Solidify partnership commitments and drive innovation aligned with customers’ business challenges.
  • Increase customer engagement with products and services and identify major political barriers to customer success.
  • Partner with more experienced team members to solve complex problems and develop strategic success plans when needed.
  • Conduct quarterly reviews of feature usage to drive adoption of tools like Journey Builder or Commerce Promotions, ensuring platform stability and performance.
  • Identify under utilization of contracted entitlements (e.g., messaging volume or GMV tiers) and align platform features with customer priorities to increase throughput.
  • Drive adoption of Tableau features with business users and analysts and track usage metrics (active users, workbook views, data source adoption).
  • Conduct enablement sessions and share best practices on dashboard creation and performance, data exploration, and visualization design.
  • Escalate complex data modeling or server confiscation questions to technical resources.
  • Use AI agents to automate routine tasks such as meeting summaries, Q  data collection, and initial health monitoring.
  • Use natural‑language commands to guide AI agents in retrieving accurate customer data and generating first drafts of success plans.
  • Use AI‑driven sentiment and intent analysis to flag early customer concerns for human intervention.
  • Actively seek out “Agent blazer” training and certifications to stay current on autonomous agent capabilities.
  • Apply product knowledge and expertise to address technical concerns and ask effective diagnosis questions.
  • Provide tailored release recommendations and monitor quarterly reviews to ensure stability, performance, and feature enhancement.
  • Serve as the primary interface for…
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