About the company
This position is listed on behalf of a partner company, who manages all applications and next steps.
Responsibilities
- Collaborate with internal teams and stakeholders to understand client objectives, business goals, and data-driven opportunities.
- Participate in consulting projects, data product development initiatives, and the creation of analytical solutions and business proposals.
- Plan and execute data collection strategies from multiple sources, including internal databases, social media platforms, and marketing campaign data using APIs, web scraping, ETL processes, and other techniques.
- Perform exploratory data analysis to identify patterns, trends, data quality issues, and relevant business insights.
- Develop predictive models using machine learning and statistical techniques to support marketing initiatives, such as customer segmentation and churn prediction.
- Design, execute, and analyze experiments to evaluate marketing strategies and improve campaign performance, including marketing mix modeling (MMM), attribution models, and causal inference approaches.
- Maintain and continuously improve developed models, ensuring accuracy, relevance, and alignment with evolving business needs.
- Communicate analytical findings and recommendations clearly to marketing teams and clients through accessible reports and presentations.
- Create data visualizations and dashboards that help stakeholders understand performance metrics and strategic opportunities.
Requirements
- Degree in Statistics or a related quantitative field.
- Previous experience with Marketing Mix Modeling (MMM) and statistical models applied to marketing is highly desirable.
- Strong proficiency in Python and R programming languages.
- Knowledge of machine learning techniques, including linear regression, logistic regression, decision trees, random forests, neural networks, and clustering algorithms.
- Ability to explore, clean, transform, and analyze large datasets while identifying data quality issues.
- Experience working with relational databases and SQL queries to extract relevant information from complex datasets.
- Knowledge of data preparation techniques, including normalization, handling missing values, and outlier treatment.
- Ability to create clear and impactful data visualizations using tools such as R, Python, Power BI, and/or Looker Studio.
- Familiarity with natural language processing techniques, including sentiment analysis, text classification, and entity recognition.
- Understanding of optimization algorithms applied to marketing challenges, such as campaign optimization, resource allocation, and customer segmentation.
- Knowledge of social media analytics methods and techniques.
- Understanding of marketing principles, digital marketing tools, analytics platforms, and media performance metrics.
- Ability to communicate technical insights effectively to both technical and non-technical audiences.
Conditions
- Flexible hybrid work model, with office visits based on business needs and no fixed minimum frequency.
- Opportunity to work as part of a collaborative data team with more than 70 professionals across different areas.
- Exposure to challenging and impactful data projects for diverse clients and industries.
- Opportunity to work with rich datasets and develop innovative analytics solutions.
- Collaborative and friendly work environment focused on knowledge sharing.
- Opportunity to expand expertise in data science, machine learning, marketing analytics, and business strategy.