Full-Time

Customer Engineer

Confirmed live in the last 24 hours

Pocus

Pocus

11-50 employees

Revenue data platform for GTM teams

Data & Analytics
Enterprise Software

Mid

Remote in USA

Work from home stipend to help you set up your home office.

Category
Data Analysis
Data Engineering
Data & Analytics
Required Skills
Python
SQL
Hubspot
Salesforce
Snowflake
Requirements
  • 3+ years of experience in sales or revenue operations, technical consulting, or solutions architect role.
  • A Bachelor’s degree or equivalent experience in a quantitative field like economics, business, math, statistics, engineering, or the hard sciences.
  • Proven technical experience with SQL, APIs and Python.
  • A proven ability to quickly learn and familiarize yourself with new concepts in a self-directed way. Examples: A client’s business model or a raw sales or financial dataset.
  • A strong business acumen combined with an analytical skillset. Comfort and fluency using data to solve problems is more important than deep knowledge of a specific tool.
  • Excellent communication in all forms. You are comfortable adjusting your style and approach to communicate technical concepts with both technical and non-technical stakeholders.
  • Endless curiosity and excitement about solving ambiguous and unstructured problems using data for external customers.
  • High levels of organization in your workflows - you understand what it means to work on multiple projects simultaneously and are able to prioritize and manage your time efficiently.
  • Nice to have: Familiarity with (or excitement to learn) integrating data via technologies like Outreach, Snowflake, Salesforce, Hubspot, Gong.
  • Nice to have: Deep understanding (or excitement to learn) common data structures, metrics, and raw data associated with B2B SaaS Salesforce implementations.
Responsibilities
  • Lead the customer implementation, including workspace development and iteration
  • Partner internally with the CS team and externally with RevOps, Data, and Go-To-Market stakeholders at world-class PLG organizations to build custom Pocus workspaces that help our customers’ accomplish their highest priority go-to-market initiatives
  • Translate business requirements into data request for customer and lead playbook brainstorm sessions
  • Conduct data modeling in Pocus to surface relevant data for customer
  • Setup initial playbooks by use case identified by customer as part of implementation
  • Custom train AI models for each customer
  • Recommend sales plays based on expertise and customer type
  • Proactively review and update customers’ workspaces to ensure value maximization and alignment to shifting priorities
  • Data: identify workspaces with poor data quality and proactively set up time to review with customer
  • Conduct iterations of workspace architecture and playbooks as new teams onboard
  • Bridge the gap between technical and non-technical stakeholders both internally and with customers
  • Support CSMs during implementation by providing a data-driven perspective on prospects’ and customers’ product-led-sales strategy
  • Drive accountability to action for the customer in the implementation process
  • Educate and transfer knowledge of Pocus architecture, data modeling and workflows to the customer’s technical admins to help them self sustain their Pocus workspace
  • Support the entire post-sales team by clearly documenting important context about each customer, their data model, and their workspace after initial implementation
  • Pass learnings and suggestions back to other internal teams as the technical voice of the customer
  • Partner with Product to provide feedback and ensure the product roadmap is informed by feedback from technical stakeholders across our customer base
  • Partner with Sales, and Customer Success to ensure a smooth handoff, paying particular attention to our customers’ data sources and making sure that the right technical stakeholders from our customers are involved for implementation

Pocus offers a Revenue Data Platform that provides businesses with insights into customer and product usage data, specifically for go-to-market (GTM) teams like sales and marketing. The platform enables these teams to analyze data without needing developers, helping them identify opportunities for conversion, cross-selling, and expansion while managing churn and improving retention. Pocus differentiates itself by simplifying data analysis, allowing users to focus on personalized customer outreach. The company's goal is to streamline growth and optimization by providing a centralized system that accelerates revenue generation.

Company Stage

Series A

Total Funding

$22.4M

Headquarters

San Francisco, California

Founded

2021

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

70%
Simplify Jobs

Simplify's Take

What believers are saying

  • Pocus' platform can significantly accelerate revenue by enabling GTM teams to quickly action product usage data.
  • The company's focus on reducing churn and boosting retention through proactive data management can lead to more stable and predictable revenue streams.
  • Partnerships with influential investors like First Round Capital enhance Pocus' credibility and provide valuable industry insights.

What critics are saying

  • The data analytics market is highly competitive, requiring Pocus to continuously innovate to maintain its edge.
  • Reliance on a subscription-based model means that customer retention is crucial; any decline in customer satisfaction could impact revenue.

What makes Pocus unique

  • Pocus focuses on democratizing data for go-to-market teams, unlike traditional data platforms that cater to more technical users.
  • The platform's ability to provide actionable insights without the need for developers sets it apart from competitors requiring technical expertise.
  • Pocus' Revenue Data Graph breaks down data silos, offering a unified view that is particularly valuable for sales, marketing, and customer success teams.

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