• Extract, query, and manipulate data using SQL from relational databases and cloud data warehouses. • Analyze large transactional and consumer datasets to identify trends, patterns, and business insights. • Build and maintain structured datasets that support recurring reports and business analyses. • Calculate key business metrics such as household penetration, market share, purchasing behavior, and category trends. • Work with raw and semi-structured data, cleaning and categorizing information as needed. • Validate data outputs and perform quality checks to ensure data accuracy and integrity. • Collaborate with internal teams to support reporting needs and answer business questions through data. • Translate complex datasets into clear findings and recommendations.

• Lead and execute analytics projects focused on patient-journey and line-of-therapy mapping, Brand analytics. • Analyze structured claims and patient datasets such as DRG, IQVIA, McKesson, Symphony claims. • Conduct exploratory data analysis (EDA) to assess treatment patterns, pathways and utilization. • Support HEOR/HCRU analyses including prevalence, burden, incidence and cost-of-illness studies. • Develop and present client-facing insights using dashboards, PowerPoint and visual analytics. • Build and optimise SQL queries, pipelines; use Excel and Python for automation and analysis. • Collaborate with HEOR, market-access, strategy and engineering teams.

Role Description We are looking for a talented and driven Senior Data Analyst to join our AdNetwork team. As a Senior Data Analyst, you will play a key role in analyzing advertising data and developing insights to optimize our platform's performance. You will work closely with the Data Analyst Team Lead to implement data strategies and mentor junior team members. - Independently identify and execute high-impact data analysis projects. - Mentor junior analysts and provide technical guidance on projects. - Design and implement A/B tests for marketing, app monetization, and product features. - Create and maintain dashboards for monitoring key advertising metrics. - Develop automated reporting solutions and data pipelines. - Collaborate with cross-functional teams to identify and solve business challenges. - Support data infrastructure improvements and maintenance. - Lead A/B testing (marketing, app monetization, product testing). Qualifications - 4+ years of experience in data analysis in the adtech, mobile, or marketing industries. - Strong proficiency in Python, SQL, and data visualization tools. - Experience in A/B testing and statistical analysis. - Experience using AI tools and LLMs (e.g., ChatGPT, Claude, Gemini). - Strong problem-solving and analytical skills. - Excellent communication skills and ability to present findings to stakeholders. - Demonstrated ability to work independently and make data-driven decisions. - Bachelor's degree in Computer Science, Data Science, Statistics, or related field. Requirements - Experience with cloud platforms (AWS) and data tools (Databricks, Grafana, Elasticsearch, Kibana). - Experience with Apache Spark and large-scale data processing. Benefits With an outstanding product and a mission that excites and inspires, Appodeal offers a unique opportunity to make an impact while being part of an amazing team. Join us and help shape the future of mobile app success!

• Lead and execute analytics projects focused on patient-journey and line-of-therapy mapping, Brand analytics. • Analyze structured claims and patient datasets such as DRG, IQVIA, McKesson, Symphony claims. • Conduct exploratory data analysis (EDA) to assess treatment patterns, pathways and utilization. • Support HEOR/HCRU analyses including prevalence, burden, incidence and cost-of-illness studies. • Develop and present client-facing insights using dashboards, PowerPoint and visual analytics. • Build and optimise SQL queries, pipelines; use Excel and Python for automation and analysis. • Collaborate with HEOR, market-access, strategy and engineering teams. Ability to gather requirements, articulate approach, timeline and execution with key stakeholders are of equal importance. • Ensure data integrity, governance, documentation and reproducibility. • Independently manage workload, communicate progress and drive project delivery.