In this leadership role, I led a team of seven data scientists while driving Ipsos’ data and analytics strategy, ensuring robust governance of data assets, and building a high-performing, value-driven team.Key accomplishments include integrating advanced analytics and machine learning techniques into product offerings, achieving a 20% increase in actionable client insights within the first year. I championed agile methodologies and best practices, streamlining project timelines and improving cross-team productivity by 25%.My expertise in custom research—spanning customer journey mapping, segmentation studies, and advanced pricing methodologies—was instrumental in delivering impactful client solutions. I also established KPIs to monitor the performance of data science initiatives, leading to a 30% improvement in project outcomes.Leveraging cutting-edge technologies such as AI and big data analytics, I uncovered new business opportunities and enhanced operational processes. Additionally, I oversaw quantitative survey research projects, including questionnaire design, sample planning, and data analysis, while supporting business development efforts that drove strategic growth for the company.

In this senior role, I led five data scientists and collaborated closely with team members in engineering, product, operations, and anomaly detection to deliver multiple projects simultaneously. My contributions include automating a manual process for data review and other data processing procedures, eliminating duplicate tasks while saving dozens of hours per week in labor. I also improved classification accuracy from 72% to 96% using regex matching, machine learning, naïve bayes, logistic regression, and decision trees to effectively consolidate and translate merged data from various data sets.

In this role, I led team members in improving the customer experience, enhancing data accuracy, and developing VBA solutions for automation. We accomplished this in part by creating a dashboarding tool to decrease time spent on daily tasks 20% while improving accuracy of project data. We also developed a new dashboard tool for syndicated reports as well as client-facing dashboards to communicate data stories to clients. As a result, we captured revenue gains and improved customer retention rates.

During this time, I led eight team members in using segmentation, regression modeling, and forecasting to identify key demographics and potential ROI in support of client projects. My contributions include creating a COVID-19 data reporting tool that significantly enhanced data accuracy and enabled data sharing with key business partners, resulting in a 50% reduction of manual data entry. I also boosted the efficiency of monthly team forecasting 40% by adopting strategic process improvements.

In this role, I led 17 researchers while working to improve team efficiency by optimizing process workflow and creating staff development plans. I worked on projects with global clients in the finance segment, including Chase, Visa, Mastercard, Schwab, UBS, and more. Highlights of my work include increasing team’s research output 15%, improving client engagement 10%, and reducing error rates from 22% to 10% by developing a new algorithm to calculated estimated mail volume. I also reduced data cleaning time 20% by creating best practices for quantitative analytical reporting and quality assurance.