Senior Analyst

Senior Analyst

WeAreParamount on a mission to unleash the power of content… you in? We've got the brands, we've got the stars, we've got the power to achieve our mission to entertain the planet – now all we're missing is… YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter – both for our audiences and our employees – and aim to leave a positive mark on culture.

Overview: We are the Global Marketing Analytics team, part of the Paramount Streaming, Data & Insights Group (DIG) team. DIG is a key connector among the Paramount Streaming verticals. The group includes subject matter experts that prototype, build, and scale data infrastructure and products. Additionally, they assess, aggregate, and analyze data while also creating narratives and insights from both qualitative and quantitative data. This work supports stakeholders by helping them make decisions, understand performance, and generate business recommendations. The Marketing Analytics team provides actionable, data-driven solutions to solve marketing challenges. We work closely with Media Strategy, Media Activation, Data Science, and Product teams to drive Paramount Streaming business growth and retention.

The Senior Analyst will help the Streaming marketing team with different initiatives. The main goals are to run experiments, measure results, and improve paid media and owned & operated (O&O) channels by using models. The role requires turning data into clear insights and recommendations. This includes using media mix modeling, cross-platform attribution tools, incrementality testing, and other advanced analytics methods. You will design and measure lift and incrementality tests to validate optimization approaches. This includes detailed analysis of media performance - the goal is to understand how model-driven optimization outperforms basic buying strategies. We will also measure the additional value provided. You will also work with the Digital O&O Promo teams. Your job will be to turn predictive models into execution frameworks and will define measurement strategies. These strategies will connect promo involvement to longer-term results, and these results include content consumption, session depth, retention, and reducing churn. A critical component of this role will be surfacing insights on when and where personalization drives diminishing returns to inform model iteration, promo strategy, and resource allocation decisions. The ability to interpret complex data and provide relevant business context to explain marketing performance and optimization impact will be key to success in this role. The ideal candidate will have good communication skills. They should be curious and detail oriented. An interest in media is important. Experience in improving marketing efficiency, testing new ideas, and using advanced measurement frameworks is also required.

Responsibilities: Foster data-informed decision making throughout the Streaming marketing organization. Design, implement, and measure incrementality and lift tests. These tests will compare targeting based on models with strategies that optimize natively on the platform. Conduct detailed analyses on media performance. Identify where model-driven optimization performs better than baseline buying strategies. Measure the additional impact. Translate predictive and targeting models into actionable strategies for Digital O&O Promo placements. Define and implement measurement frameworks. These frameworks will connect promo involvement to results. These results include content starts, session depth, retention, and reducing churn. Analyze marketing and attribution data, which helps measure the return on marketing investments. You will also optimize how budgets are allocated. Additionally, provide recommendations for different channels and partners. Use analyses across platforms, experimentation, and outputs from media mix models. Identify and explain the limits of personalization and targeting strategies. Know when these strategies stop being effective. Use this knowledge to enhance models and update promotional strategies. Partner closely with internal data science teams and external partners to enhance and increase relevance and actionability of results across various media channels. Collaborate with team members to ensure dimensions and metrics in data pipelines are compliant with business workflows powering marketing reporting. Support development of auditing tools of existing data sets to check for anomalies and irregularities; leverage SQL and Google Cloud Service suite features to escalate data inconsistencies. Build and refine data workflows for Streaming marketing data to ensure consistent data integrity. Improve and strengthen marketing data pipelines in partnership with data engineering teams. Support ad hoc analysis to provide deeper and more granular insights on media and promo performance. Additional other duties and responsibilities, as assigned.

Basic Qualifications: BA/BS. 3+ years' experience in digital marketing and analytics, web analytics, or online media industry. Proficient in SQL with a thorough knowledge of data and systems' infrastructures; experience extracting, cleaning, and transforming data from databases using SQL. Experience or coursework in media measurement including web, native app, video measurement technology and standards. Experience designing and analyzing incrementality, lift, or A/B tests. You should know how to use various tools and languages for data analysis, reporting, and visualization. These include Excel, Microsoft Office, Google Collaborative Apps like Docs, Sheets, and Slides, as well as Tableau, R, and Python. Strong detail-orientation with a penchant for data accuracy and good grammar.

Additional Qualifications: Strong mathematics and statistics background. Experience working with predictive models and personalization frameworks in marketing contexts. Strong solutions-oriented and critical thinking mindset. Experience using Google Cloud Platform (BigQuery). You should have experience turning requirements into clear instructions, then creating documentation based on those instructions. Experience working autonomously to meet deliverables with some oversight. Experience using project management tools like those from Atlassian (JIRA, Confluence).