Senior Analytics Engineer

As a Senior Analytics Engineer at Novo, your key responsibilities will include designing and conducting data-driven experiments to enhance customer acquisition, lifetime value, and engagement. You will collaborate with cross-functional teams to strategize marketing efforts, oversee campaign launches, manage budgets, and identify growth opportunities through thorough data analysis.

To qualify for the Senior Analytics Engineer role at Novo, you should hold a bachelor’s degree in a quantitative field like Economics, Statistics, or Computer Science. Additionally, having 2-4 years of experience in data analysis and proficiency in SQL, as well as strong analytical and communication skills, will prepare you well for this position.

Novo is committed to supporting the professional growth of its Senior Analytics Engineers through learning and development budgets. This allows you to pursue further education, training, or bonding activities with your team, fostering an environment where continuous improvement and growth are prioritized.

At Novo, the work culture is positive, inclusive, and supportive. As a Senior Analytics Engineer, you can expect to work in a collaborative environment where your ideas are valued, and there's a strong emphasis on camaraderie, making it a great place to grow and contribute meaningfully.

In the Senior Analytics Engineer role at Novo, your success will be measured by your ability to employ data analytics efficiently to identify growth opportunities and implement strategies that improve customer acquisition, lifetime value, and engagement, alongside achieving designated key performance indicators (KPIs).

When designing experiments for marketing initiatives, I start by clearly defining objectives and hypotheses. It's important to determine what metrics to measure success, ensuring alignment with overall business goals. I then select appropriate methodologies, whether it's A/B testing or multivariate testing, and create a detailed plan to execute and monitor the experiments effectively.

I have extensive experience using SQL to analyze complex datasets and generate insights for data-driven decisions. In my previous role, I created various queries to extract key metrics for campaigns, performed data cleaning, and wrote reports that highlighted trends and patterns, which informed strategic marketing initiatives.

In previous positions, I've employed several strategies to optimize customer acquisition, including detailed audience segmentation to tailor marketing messages, leveraging A/B testing to refine ad copy and targeting, and optimizing bidding strategies based on customer lifetime value to allocate budget effectively, ensuring maximum return on investment.

One challenging project involved analyzing a large dataset to identify factors impacting customer churn. I systematically approached this by cleaning the data, employing statistical techniques to isolate key variables, and utilizing visualizations to present the findings to stakeholders, ultimately leading to actionable insights that reduced churn rates significantly.

To ensure my analysis is understandable to non-technical stakeholders, I focus on clarity and visual representation. I translate complex data into simple narratives, often utilizing charts and dashboards to illustrate key points and ensuring that I connect findings to business implications, making it relevant to their context.

A test-and-learn culture is crucial in analytics because it encourages experimentation and learning from results rather than relying solely on assumptions. This culture fosters innovation and agility, allowing teams to adapt strategies based on real data, leading to better decision-making and ultimately enhancing customer experiences.

I frequently use tools like SQL for querying databases, Python for data manipulation and analysis, and Tableau for visualization. Each tool serves its purpose: SQL is great for handling large datasets efficiently, Python offers versatility in analysis and automation, while Tableau excels in creating interactive and easily digestible visual reports.

When managing multiple responsibilities, I prioritize projects based on their alignment with strategic goals and their potential impact on business outcomes. By assessing urgency and resources available, I create a flexible timeline and ensure regular communication with stakeholders to keep everyone on the same page.

Communication is a critical aspect of analytics work. It ensures that insights derived from data are effectively shared with relevant parties. I prioritize clear and concise communication, tailoring my message for various audiences so that findings can be acted upon efficiently, enhancing collaboration across teams.

My motivation to work as a Senior Analytics Engineer at a startup like Novo stems from the opportunity to make a significant impact in a fast-paced environment. I thrive on the challenges that come with innovation, and contributing to a mission that empowers small businesses aligns perfectly with my professional values and goals.