Our client is a globally recognized innovator in the IoT space, delivering solutions focused on retail loss prevention, operational visibility, and advanced analytics. Their headquarters is located in South Orange County, California, and they maintain a significant international footprint with offices throughout the UK, Australia, China, Hong Kong, Germany, France, and Canada.
They are actively looking to bring on a Senior Data Scientist / Analytics & Machine Learning Engineer with strong capabilities in SQL, Python, business intelligence, dashboard development, and predictive analytics.
This role is instrumental in expanding the company's analytical maturity beyond standard reporting by introducing forward-looking models, operational intelligence, customer insight frameworks, and scalable data solutions that enable proactive business decisions and measurable impact.
The ideal candidate is both technically strong and business-minded, with the ability to translate complex data into meaningful insights, communicate clearly with stakeholders, and collaborate across departments to address both operational and customer-focused challenges.
Role & Responsibilities Customer & Operational Analytics:
- Examine customer data, operational metrics, monitoring outputs, video classification results, and theft-related information to surface patterns, risks, and actionable opportunities.
- Develop structured analytical approaches to assess product adoption, customer engagement, operational efficiency, and overall value delivery.
- Enable more proactive customer engagement through data-backed insights and trend identification.
- Work closely with leadership to enhance transparency into both operational effectiveness and customer performance indicators.
Predictive Modeling & Data Science:
- Create, deploy, and maintain predictive models focused on areas such as theft behavior, customer usage patterns, operational risk factors, service performance, and escalation triggers.
- Build forecasting and trend analysis solutions to support planning, forecasting, and customer success strategies.
- Leverage statistical techniques, machine learning models, and advanced analytics methods to drive better business outcomes.
- Continuously monitor, tune, and improve model accuracy, relevance, and overall performance.
Business Intelligence & Visualization:
- Design and build dashboards, KPI tracking tools, and reporting solutions using platforms like Power BI, Tableau, or comparable technologies.
- Produce executive-level reports and operational scorecards that support high-level strategic planning.
- Automate manual reporting processes and enhance the scalability of visualization and analytics tools.
- Convert complex datasets and analytical outputs into clear, concise, and actionable business insights.
Cross-Functional Collaboration:
- Partner with teams across Operations, Customer Success, Sales, Product, IT, Engineering, and Finance to identify high-impact opportunities and prioritize analytics initiatives.
- Contribute to projects involving AI-based analysis, workflow automation, and operational efficiency improvements.
- Collaborate with engineering and data teams to improve data integrity, accessibility, system integration, and governance practices.
Must Have Skills: - Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, or a related discipline.
- 4-8 years of hands-on experience in data science, predictive analytics, customer or operational analytics, or similar roles.
- Demonstrated experience building predictive models and performing sophisticated data analysis in a business environment.
- Advanced SQL expertise along with strong proficiency in Python or related programming tools.
- Experience using business intelligence platforms such as Power BI, Tableau, or similar tools.
- Experience working with large-scale, complex datasets across operational and customer domains.
- Strong analytical thinking, problem-solving capabilities, and attention to detail.
- Excellent communication skills with the ability to clearly explain technical findings to non-technical stakeholders.
- Proven ability to work independently while managing multiple priorities in a dynamic environment.
- Education And/Or Experience : BSEE, MSEE, BSCS, or MSCS
Nice to have / Preferred Skills: - Exposure to SaaS environments, retail technology, video analytics, loss prevention systems, IoT platforms, subscription-based services, or service-driven organizations.
- Understanding of machine learning techniques, AI-enabled analytics, and operational optimization approaches.
- Experience working with cloud-based ecosystems such as Azure, AWS, or Google Cloud.
- Background in developing executive-level dashboards and KPI reporting frameworks.
The Offer - Competitive total compensation package ranging from $130K-$160K
- Comprehensive benefits package including medical, dental, and vision coverage; Life/ADD/LTD insurance; FSA/HSA offerings
- 401(k) plan with company match
- Generous paid time off program
- 11 paid company holidays
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