The successful candidate will be responsible for designing, modeling, testing and analyzing MIS research and outreach data. The goal is to identify patterns and insights that will aid in understanding and improving research and customer engagement behavior within our MIS Researchteam.

Key Responsibilities:

1. Prepare clear and concise data reports and visualizations for stakeholders.
2. Ensure data accuracy and integrity through rigorous quality control measures.
3. Data Collection and Design:
1. Design and Implement Data Sets: Collaborate with cross-functional teams to design and create robust data sets that capture relevant metrics related to our content performance, user behavior, and market trends.
2. Data Collection Strategies: Develop innovative approaches for collecting data from various sources, including web analytics, social media, and user interactions.
3. Quality Assurance: Ensure data accuracy, consistency, and reliability through rigorous quality checks.
4. Quantitative Analysis:
1. Statistical Modeling: Apply advanced statistical techniques to analyze data and extract actionable insights. Utilize tools such as R (or Python) for modeling and hypothesis testing.
2. Segmentation and Personalization: Identify audience segments with supervised and unsupervised methods based on behavioral patterns and preferences. Tailor strategies to enhance engagement within each segment.
3. A/B Testing: Design and execute A/B tests to optimize content delivery, user experience, and conversion rates.
5. Content Optimization:
1. Content Performance Metrics: Evaluate the effectiveness of our content campaigns using KPIs such as click-through rates, time spent on page, and conversion rates.
2. Recommendations: Provide data-backed recommendations to improve content quality, distribution channels, and targeting strategies.
3. SEO Insights: Collaborate with SEO teams to enhance content visibility and organic search rankings.
6. Strategic Decision-Making:
1. Business Impact Assessment: Quantify the impact of strategic initiatives on readership and engagement.
2. Forecasting and Predictive Analytics: Develop and train neuronal and machine and deep learning models to predict future trends and guide strategic planning.
3. Competitor Analysis: Monitor industry trends and competitor performance to inform our marketing strategies.
7. Collaboration and Communication:
1. Cross-Functional Collaboration: Work closely with editorial, product, and technology teams to align marketing efforts with overall business goals.
2. Clear Reporting: Present findings and insights to stakeholders in a concise and actionable manner.

Qualifications:

1. Bachelor’s or Master’s degree in Data Science, Statistics, or a related field.
2. 10 years of proven experience as a Data Scientist or similar role.
3. Strong analytical mindset with the ability to translate data into actionable recommendations
4. Strong knowledge of data modeling, training predictive models, data mining, and segmentation techniques.
5. Proficiency in relevant statistical, data analysis tools and programming languages (e.g., R, RStudio, SQL, Python, MiniTab or other).
6. Familiarity with BI technologies (e.g., Microsoft Power BI, Tableau).
7. Excellent analytical and problem-solving skills.
8. Exceptional communication skills to effectively collaborate with the team and present findings to stakeholders.

Preferred Skills:

1. Experience in the financial services or publishing sector.
2. Knowledge of MIS systems and their datastructures. See Less