Senior Data Scientist - Customer & Operational AnalyticsLocation: Gatekeeper Systems Headquarters - Foothill Ranch, California
Reports To: VP, Operations & Service
Position SummaryReporting directly to the VP of Operations & Service, this role will focus on transforming customer, operational, monitoring, video classification, subscription, and theft-related data into actionable insights that improve customer outcomes, operational performance, service delivery effectiveness, and business growth.
This individual will play a key role in advancing the company's analytics capabilities beyond traditional business intelligence by developing predictive models, operational analytics, customer intelligence frameworks, and scalable reporting solutions that support proactive decision-making and measurable business impact.
The ideal candidate combines strong technical and analytical expertise with the ability to understand business operations, communicate insights effectively, and partner cross-functionally to solve complex operational and customer challenges.
Key ResponsibilitiesCustomer & Operational Analytics:- Analyze customer, operational, monitoring, video classification, and theft-related data to identify trends, risks, opportunities, and actionable insights.
- Develop analytical frameworks to measure customer utilization, operational effectiveness, subscription adoption, and customer value realization.
- Support proactive customer engagement strategies through data-driven insights and trend analysis.
- Partner with leadership teams to improve visibility into operational and customer performance metrics.
Predictive Modeling & Data Science:- Design, build, and maintain predictive models related to theft trends, customer behavior, operational risks, service utilization, and escalation indicators.
- Develop forecasting and trend analysis models that support operational planning and customer success initiatives.
- Apply statistical analysis, machine learning, and advanced analytics techniques where appropriate to improve business outcomes.
- Continuously evaluate and refine model performance and business relevance.
Business Intelligence & Visualization:- Develop dashboards, KPI reporting, and analytics tools using Power BI, Tableau, or similar platforms.
- Create executive-level reporting and operational scorecards that support strategic decision-making.
- Automate reporting and improve scalability of analytics and data visualization capabilities.
- Translate complex analytical findings into clear, business-oriented recommendations.
Cross-Functional Collaboration:- Partner closely with Operations, Customer Success, Sales, Product Management, IT, Engineering, and Finance teams to identify business opportunities and analytics priorities.
- Support initiatives involving AI-driven analytics, workflow automation, and operational optimization.
- Collaborate with technical teams to improve data quality, accessibility, integration, and governance across systems and platforms.
QualificationsRequired:- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, or related field.
- 4-8 years of experience in data science, predictive analytics, customer analytics, operational analytics, or related analytical roles.
- Strong experience developing predictive models and performing advanced data analysis in business environments.
- Advanced proficiency in SQL and experience with Python or similar analytics/programming languages.
- Experience with Power BI, Tableau, or similar business intelligence and visualization tools.
- Experience working with large, complex operational and customer datasets.
- Strong analytical, problem-solving, and critical-thinking capabilities.
- Excellent communication and presentation skills with the ability to explain technical concepts to business stakeholders.
- Ability to operate independently and manage multiple priorities in a fast-paced environment.
Preferred:- Experience in SaaS, retail technology, video analytics, loss prevention, IoT, subscription-based services, or service-oriented organizations.
- Familiarity with machine learning, AI-driven analytics, and operational optimization techniques.
- Experience with cloud-based data platforms such as Azure, AWS, or Google Cloud.
- Experience supporting executive-level operational reporting and KPI development.
Success Metrics:- Improved visibility into customer utilization and operational performance
- Actionable theft and customer intelligence insights
- Increased predictive capabilities across operations and customer engagement
- Improved subscription adoption and customer retention analytics
- Increased effectiveness and adoption of dashboards and reporting tools
- Development of scalable analytics and predictive modeling capabilities
