Data Scientist, Marketing Job at Captions in Los Angeles

As a Data Scientist in Marketing at Captions, you'll be responsible for automating marketing reporting, building data pipelines from platforms like Facebook and Google into a centralized warehouse, and developing dashboards for comprehensive campaign performance analyses. You'll also work closely with Finance and Marketing teams to monitor essential metrics such as CAC and LTV, and design incrementality testing to measure marketing effectiveness.

To qualify for the Data Scientist position at Captions, candidates should ideally hold a Bachelor’s or Master’s degree in a quantitative field. Additionally, having at least 5 years of relevant experience in marketing analytics and a deep understanding of marketing metrics are critical. Proficiency in Python, SQL, as well as familiarity with marketing measurement tools like Google Analytics is highly preferred.

Success for the Data Scientist role at Captions is defined by your ability to provide strategic insights from data that drive marketing decisions and ROI. This includes developing effective reporting tools, measuring marketing performance accurately through metrics such as CAC and LTV, and ultimately enhancing the effectiveness of our marketing strategies across various channels.

In the Data Scientist role at Captions, you will work with a variety of tools and technologies, most notably Google Analytics, Google Ads, Facebook, and Python for data analyses. Experience with BigQuery and data visualization tools will also be beneficial as you create automated reports and dashboards for stakeholders across the company.

The work environment for a Data Scientist in Marketing at Captions is dynamic and collaborative. You will be part of a passionate early team that values creativity and innovation. The culture promotes open communication and cross-functional engagement, allowing you to make a significant impact on both products and strategies for the company.

To automate marketing reports at Captions, I would begin by identifying the key metrics required by the Marketing team and understanding the existing reporting processes. Utilizing my skills in SQL, I would build queries to extract data from various ad platforms and centralize it in our data warehouse. Then, I'd utilize data visualization tools to create interactive dashboards that provide easy access to these reports for stakeholders.

A multi-touch attribution model evaluates the influence of multiple marketing touchpoints across the user’s journey before a conversion occurs. It provides insights on how different channels contribute to overall customer acquisition and helps allocate budgets effectively. In the role at Captions, I would leverage data from various platforms to create an in-house multi-touch attribution model to enhance our marketing efforts.

I have extensive experience in building data pipelines that automate the flow of information from various ad platforms into a centralized system. At my previous job, I constructed ETL processes utilizing Python and SQL, which not only streamlined data access but also improved the accuracy of our marketing reports, enabling swift data-driven decision-making.

Defining KPIs begins with aligning them with the overall business objectives. At Captions, I would work closely with marketing and finance teams to establish clear metrics like CAC and LTV. Monitoring these KPIs involves setting up alerts for significant shifts and leveraging visualization tools for ongoing analysis, which allows us to identify trends and adjust strategies proactively.

My approach to A/B testing involves clearly defining the objectives and hypotheses first. Then, I create two versions of a campaign to test varying elements such as ad copy or visuals. After implementation, I analyze the results through statistical methods to determine significance. At Captions, I would ensure that A/B test findings are documented to enhance future marketing initiatives.

Ensuring data integrity involves establishing a standardized process for data collection from different marketing channels. This includes validating data as it is ingested into the data warehouse and conducting regular audits. I would also use automated scripts to detect anomalies, ensuring the accuracy and reliability of our insights at Captions.

I possess a strong foundation in statistical analysis, having utilized techniques such as regression analysis and hypothesis testing extensively. This background enables me to derive meaningful insights from datasets, which is particularly valuable for assessing marketing performance and informing decisions as a Data Scientist at Captions.

User segmentation is crucial in marketing analytics as it allows us to tailor strategies to specific audience groups. By analyzing behavior, demographics, and preferences, I can identify trends and optimize campaigns to improve engagement and conversion rates. At Captions, I would utilize segmentation to refine our marketing approaches and maximize ROI.

Staying updated on marketing analytics trends involves regularly engaging with industry publications, attending webinars, and participating in online forums. Networking with other professionals in the field and experimenting with new tools are also effective ways to remain informed about the latest advancements, which I would leverage in my role at Captions.

My skill set aligns well with the Data Scientist position at Captions due to my extensive experience in marketing analytics and data manipulation. My proficiency in Python and SQL allows me to efficiently analyze large datasets, while my deep understanding of marketing metrics ensures I can deliver actionable insights that drive business results.