Re-skilled
analysts, BI professionals, and developers into data scientists
A Fortune 100 company partnered with Galvanize to empower analysts and developers to drive predictive modeling and retention strategies.
Key Outcomes
Modernized
data modeling practices across multiple business units
Context
Tackling the Challenge of Legacy Infrastructure Issues
A Fortune 100 company with nearly a century of operations faced mounting challenges within its compliance department due to process inefficiencies and inconsistent data across systems — symptoms of legacy infrastructure and siloed analytics. The company identified a critical gap: its existing teams lacked the skills to leverage predictive analytics, modern data science methods, and state-of-the-art tooling to transform raw data into actionable insights.
Strategically, leadership recognized that improving customer retention, anticipating complaint patterns, and driving efficiency depended on building internal capability, not just buying external tools or talent.
Our Approach
Collaborate
Galvanize began with a comprehensive assessment of the company’s existing data analytics workforce. Stakeholder interviews and skills diagnostics revealed limited predictive modeling capabilities, low adoption of modern tooling, and siloed data practices across departments.
Translate
Based on these findings, Galvanize designed a customized Data Science Core program aligned with the company’s specific datasets, business questions, and operational goals. The curriculum focused on hands-on, role-based learning to upskill analysts, BI professionals, and developers into data scientists who could deliver measurable business impact.
Innovate
The delivery was structured through immersive cohorts that blended instruction, hands-on labs, and applied projects tied directly to real business problems. Students collaborated with their managers to identify high-value datasets and define projects with clear ROI potential. Each team worked in an Agile environment with embedded instructors, ensuring learning translated into production-ready solutions. Many of these capstone projects were prototyped during training and moved into production shortly after program completion.
Validate
Throughout the program, Galvanize employed formative assessments and weekly reporting to track progress and maintain accountability. Learning objectives were tied to performance metrics, enabling both instructors and business stakeholders to measure skill acquisition and project advancement.
Impact
The upskilling initiative delivered immediate and measurable outcomes for the organization. Analysts, BI professionals, and developers evolved into data scientists who began contributing strategic value before program completion.
Capstone projects drove significant operational and retention outcomes:
- Operational Efficiency: Classification systems were developed to route incoming service requests to optimal operators, improving resolution speed and customer satisfaction.
- Customer Retention: Predictive models identified when customers were likely to disengage, enabling proactive outreach and improved retention.
- Risk and Compliance: Models detected anomalous behaviors and trends, enabling earlier interventions and reducing exposure.
- Behavioral Insight: Pattern recognition and time-series forecasting were used to anticipate usage trends and guide business decisions.
Senior leadership attended the capstone presentations and recognized the scale of value unlocked. Following the program, multiple participants were formally redeployed into predictive modeling roles, and the company committed to an ongoing investment in data science upskilling.
Client Voice
Let’s Collaborate
Galvanize helps organizations build internal technical capability that turns strategy into execution. By combining customized curriculum, applied learning, and embedded coaching, we help enterprises modernize faster and achieve measurable business outcomes.
Talk to us about scaling data science and predictive analytics capabilities inside your organization.