Big Data Analyst & Marketing Data Scientist

We are seeking an experienced senior professional to lead data collection and analysis for marketing campaigns across multiple industry sectors. In this role, you will harness AI tools and advanced statistical methods to turn large, complex datasets into actionable insights that drive marketing strategy. You will build and analyze big data pools from various sources, develop predictive models, and present data-driven narratives that inform decision-making.The ideal candidate thrives at the intersection of data and storytelling, collaborating with cross-functional teams to optimize campaigns and support business goals with evidence-based insights.

Job Description

As a Marketing Data Scientist / Big Data Analyst , you will play a pivotal role in our agency by managing end-to-end data initiatives for marketing campaigns in diverse sectors. This includes developing methods to collect and aggregate large datasets from numerous digital sources , then cleaning and processing that data to uncover meaningful patterns

You will transform raw data into clear graphs, statistical reports, and insightful visualizations that aid in decision-making Using AI-driven analytics and machine learning models, you will generate predictive insights and optimization recommendations to improve campaign performance. Your work will directly influence marketing tactics such as lead generation strategies, business planning, and branding efforts by providing deep analytical reports and forecasts. In collaboration with marketing teams, you’ll help set targets and KPIs, ensuring that data-driven insights are integrated into strategic planning. Ultimately, you will be responsible for leveraging cutting-edge analytics to drive marketing strategies and enhance campaign effectiveness across the organization

Key Responsibilities

• Data Collection & Management: Develop and implement robust data collection methods to gather large-scale data from relevant industries and digital platforms. Build and maintain big data repositories combining sources like web analytics, CRM systems, social media, and more ensure data quality through cleaning and validation processes for accurate analysis.
• Data Processing & Visualization: Utilize tools such as Python (pandas, NumPy) and Excel to process and analyze the collected data. Generate clear visualizations (charts, graphs) and performance reports to communicate key metrics and trends regularly prepare monthly/quarterly KPI reports using software like Excel and Power BI, translating complex datasets into easily understandable dashboards.
• Advanced Analytics & AI Integration: Leverage artificial intelligence and machine learning techniques to extract deeper insights from marketing data. Build predictive models to forecast marketing performance and customer behavior, and analyze campaign data to uncover actionable insights using AI/ML techniques use predictive analytics to solve complex marketing problems and drive data-informed business decisions.
• Campaign Optimization: Apply advanced statistical analysis to evaluate campaign outcomes and identify opportunities for improvement. Develop audience segmentation models and personalization strategies to help target the right audiences at the right time provide optimization recommendations (e.g. timing, channel mix, budget allocation) based on data findings to maximize ROI on marketing campaigns.
• Reporting & Insights Communication: Extract data from platforms like Google Analytics and Meta (Facebook/Instagram) Business Suite to assess campaign performance across digital channels. Prepare comprehensive analysis reports on key areas such as lead generation funnels, marketing ROI, and brand engagement, presenting findings to stakeholders in a clear narrative format. Present data-driven insights and recommendations to marketing and leadership teams, translating analytic results into concrete action items.
• Collaboration & Strategy Support: Work closely with marketing, sales, and business planning teams to define campaign goals and key performance indicators (KPIs) . Partner with cross-functional teams (including product and IT) to ensure analytical findings inform strategic decisions and to implement data-driven improvements support the development of innovative marketing strategies by providing thought leadership on data and emerging trends.
• Automation & Tool Development: Identify opportunities to automate data extraction, reporting, and analysis processes using AI and scripting. Develop and maintain interactive dashboards (e.g., in Tableau or Power BI) to allow stakeholders self-service access to marketing analytics. Continuously research and integrate new data tools or methodologies to enhance the analytics workflow and efficiency.
• Continuous Improvement: Stay up-to-date with the latest industry trends in marketing analytics, big data technologies, and AI applications. Monitor the effectiveness of data mining and analytics tools in use, troubleshooting any issues that arise proactively recommend and implement enhancements to data practices, ensuring our analytics approach remains cutting-edge and effective in driving marketing success.

Required Qualifications

• Experience: 7+ years of relevant experience (senior level) in data science, marketing analytics, or a related field. Proven track record of leveraging data analysis to drive significant business impact and marketing ROI experience in managing large-scale data projects from inception to insight delivery.
• Digital Marketing Analytics: Hands-on experience analyzing digital marketing performance using platforms like Google Analytics (or Adobe Analytics) and social media advertising tools (Facebook/Instagram Ads Manager, Google Ads, etc.). Deep understanding of web analytics and marketing metrics to independently evaluate campaign success.
• Technical Skills: Advanced proficiency in Python for data analysis (including libraries such as pandas and NumPy) and Excel (complex formulas, pivot tables) for data manipulation. Strong ability to query and handle databases using SQL and/or to perform statistical analysis in tools, familiarity with statistical software or languages (e.g., R, SAS) is a plus.
• AI & Machine Learning: Working knowledge of AI and machine learning techniques as applied to marketing data. Experience building or utilizing ML models for predictive analytics, customer segmentation, or personalization in a marketing context awareness of AI-driven marketing tools (such as optimization algorithms, chatbots, or recommendation engines) and ability to integrate these into analysis workflows.
• Big Data & BI Tools: Comfortable working with large datasets (“big data”) from varied sources. Experience using data visualization and business intelligence tools like Power BI or Tableau to create interactive dashboards and reports for stakeholders knowledge of data warehousing concepts and ability to extract data from data warehouses or big data platforms is preferred.
• Analytical & Problem-Solving Skills: Exceptional analytical thinking and problem-solving abilities, with a talent for identifying trends and insights in complex data ability to design experiments (A/B tests, multivariate testing) and apply statistical rigor to interpret results. A data-driven mindset and attention to detail in validating findings.
• Communication & Storytelling: Excellent communication skills to translate data findings into compelling stories and presentations for both technical and non-technical audiences. Proven ability to communicate insights and recommendations to all levels of an organization, aiding strategic decision-making.
• Leadership & Collaboration: Demonstrated ability to lead projects and possibly mentor junior analysts or data team members. A collaborative attitude to work effectively with cross-functional teams. (Leadership experience in guiding analytics initiatives or teams is a strong plus, indicating the ability to manage resources and drive a data-focused culture)
• Language Proficiency: Proficiency in English (written and spoken) is required. You should be comfortable reading and writing technical documentation in English and communicating findings to international stakeholders.
• Education: Bachelor’s or Master’s degree in a relevant field such as Statistics, Data Science, Computer Science, Engineering, Mathematics, Economics, or Marketing a strong foundation in quantitative analysis is essential. Advanced degrees or relevant certifications in data analytics or marketing science are advantageous.

Our agency works on multi-sector projects, so we value candidates who are adaptable and curious about different industries , and who can apply data-driven marketing strategies in new domains. If you are an innovative thinker who stays on top of emerging trends and enjoys turning data into strategic insights, we encourage you to apply.