Elena Dyachkova, Sr. Data Manager, on Successfully Career Pivoting from Sports to Product Analytics

Elena Dyachkova, Sr. Data Manager at Bubble, is a Russian born and raised data professional who migrated to the U.S. to pursue new heights in her career. Elena’s journey is truly an inspiration to those who may be considering a career transition. While Elena has developed a strong expertise in the world of product analytics, that was not her initial career path. While back home in Russia, Elena actually kicked off her career in the world of sports for organizations including the Russian Athletics Federation as a Development Manager and IAAF World Championships 2013 as a project manager. She even pursued sports related roles as she kicked off her career in the U.S. by performing social media and analyst related work. 

Data Analyst at Repucom (Acquired by Nielsen)

After graduating from NYU, Elena’s first role after grad school was with Repucom, a global leader in sports measurement, evaluation and intelligence. This company was then acquired by Nielsen, where she continued to work in the realm of data. In this role, she held key responsibilities including:

• Conducting sports sponsorship ROI evaluations by overlaying technology 
• Analyzing TV ratings data to determine the revenue generated from sports sponsorships

Unfortunately, the role started to become extremely repetitive and less impactful over time. At this point, Elena was ready to GO!

Analyst, People Analytics at Xaxis

Once Elena realized that she was exhausted by the repetitive tasks at Nielsen, she moved on to a role as an Analyst, People Analytics at Xasis, an advertising company owned by GroupM. This was her first role no longer working in sports! What made it even more of an extraordinary experience was the fact that she was the first person in the company to manage people analytics. This job would require her to utilize data for HR decisions such as hiring, compensation, retention, and talent development.

As interesting as that sounds, it did come with its own share of challenges. She would ultimately have to face budget freezes, limiting the impact of her role and thus watching a role she was once very excited about become less engaging and less impactful. She even ended up having to perform administrative tasks due to staffing shortages. This was the moment she realized it was time to take on new challenges.

Sr. Product Management Analyst at comScore

Did someone scream, competition? Oh yes! Elena kicked things up a notch by pursuing a product analytics role at Nielsen’s competition, ComScore, a software company that allows media buyers and sellers to quantify multi-screen behavior and make business decisions with confidence. When Elena first joined the company, she was placed in a client services role assisting customers with making sense of data and methodologies. She then transitioned over to the product team. This was a huge learning curve for her. In this role, she was exposed to product management, learned about agile methodologies, worked with engineers and launched numerous products. The highlight of that job was participating in a high-budget project with Google in several foreign markets.

Sr. Manager, Product Analytics at Peloton

The infamous Peloton! During the pandemic, it seemed as if everyone wanted a Peloton. However, Elena had an interest in the company even before the pandemic. In 2018, she started a role as a product analyst, there. Initially, she had limited knowledge on product management and SQL from her prior role. However, Peloton created an environment for her to grow. While on the job, she strengthened her SQL skills and even found herself embraced by a collaborative and innovative work environment. Throughout her journey at the company, she grew from serving as an individual contributor to managing a team of 15 people with diverse specialties. 

Associate Director of Data Science at Spring Health

It is evident that her first role in the wellness and fitness space inspired her to conquer new businesses within this industry. In this case, she joined Spring Health, a mental health care platform, as their Associate Director of Data Science. She was their first Product Analytics Lead. In this role, she led internal experiments and established processes for working with the product team. Over time, she also took on responsibilities across the entire data stack, including data ingestion and business intelligence.

While Elena’s path in the world of data was an interesting one, there are so many ways to navigate the industry. You just have to stay focused and be willing to take on new challenges. Elena mentions; 

You should have a set of data skills and traits that make for a good product manager. In the world of product analytics, you aren't necessarily going deep on building and refining machine learning models and intricate real time data processing pipeline. There is room for different levels of engaging with and manipulating data.This career is good for someone who is a little bit scattered and skilled at having their  ear to the ground and figuring out what's going on. This is for someone thinking about how to put different pieces together and make something meaningful out of it.

Want insight into the day-to-day of a product analytics role? Check it out:

Contextual Understanding

• Digesting a lot of context related to the product roadmap, outcomes of concept tests, and qualitative user feedback from various channels (surveys, support tickets).
• Balancing this context to shape prioritization and specific projects.

Observing Product Metrics

• Spending time each week observing and internalizing product metrics.
• Analyzing how different parts of the product and the customer journey interact with one another.
• Developing a mental model to understand what works, what doesn't, and identifying levers for improvement.

Data Work

Engaging in actual data work, which involves two main buckets:

• Tactical Work: Involves tasks closely tied to the product roadmap, such as preparing for the launch of experiments or new features. This is for determining data collection methods, defining metrics, setting experiment durations, and building dashboards.
• Generative Work: This is based on user research, qualitative feedback, and metric analysis, generating ideas for further research. This is for prioritizing ideas based on business impact and selecting which ones are worth pursuing.

Marinating Recent Trends

• Setting aside time regularly to marinate recent trends, keeping up with changes/developments in the product, and market landscape.

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Problem Solving and Exploratory Analysis

• Identifying trends or changes in user behavior that may require further exploration.
• Conducting exploratory analysis to understand the reasons behind certain trends or specific user feedback.

As a leader in this space, Elena recognizes the importance of collaboration and team leadership. She outlines key points about her relationship with company stakeholders: 
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Collaboration with Teams

• Works closely with data scientists, marketing, and product teams.
• Recognizes the necessity for close collaboration at both the team and leadership levels.

Leadership Alignment

• Acknowledges the idea that for projects requiring collaboration between teams, leadership collaboration is equally essential.
• Reflects on the need for senior leadership alignment to facilitate successful team collaborations.

Responsibilities as a Senior Leader

• Ensures her team is focused on high-impact tasks aligned with business goals.
• Recognizes the multitude of tasks possible in the data world and prioritizes those with immediate business impact.

Understanding Leadership Priorities

• Acts as a bridge between her data team and cross-functional leadership (product, finance, marketing, and sales).
• Maintains a close understanding of top-of-mind issues for leadership and their specific data needs.

Role in Decision-Making

• Identifies areas where data points can expedite decision-making processes for leadership.
• Ensures that the data team is aligned with the business objectives and provides relevant insights for effective decision-making.

Systematizing Feedback

• Systematizes and digests feedback from cross-functional leadership.
• Relates pertinent information to direct reports, guiding them in focusing on tasks that align with organizational priorities.

Facilitating Collaboration

• Points direct reports to the right people for effective collaboration.
• Ensures that there is a smooth flow of information and collaboration between her team and other functional areas.

Syncing with the Right People

• Establishes sync points with the right individuals within leadership to facilitate collaboration.
• Aims to create a cohesive and collaborative environment at both the team and leadership levels.

Words of motivation from Elena? She suggests,

To build a career in data, you need to try to solve real problems. It does not require attending a fancy data science bootcamp that you will need to pay a lot of money for. A lot of times people will do a bootcamp and receive data sets that are already cleaned, modeled out, and are there just for you to practice your Python. But what's the use case for that? You want raw data to toy with.

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Interested in connecting with Elena? You can find her on LinkedIn, here.

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Interested in making a career pivot into a business and tech role? Check out these two resources I created for professionals like you:

25 In-Demand Business & Tech Roles for 2024

16 Journal Prompts for Pivoting into Business & Tech Roles