Recruiting Data Scientist for cyberFolks

1. challenge: who Cyberfolks was looking for and why this recruitment was crucial

Cyberfolks is a fast-growing technology company specializing in online services and e-commerce. Due to the intensive development of digital products and the growing number of users, the company faced the challenge of further optimizing its data-driven operations. A key goal was to increase ARPU (Average Revenue Per User), or average revenue per user, and make better use of data in decision-making processes.

In response to these needs, Cyberfolks' management decided to hire an expert who would combine analytical competencies with a business understanding of the e-commerce market. The person sought was to fill the position of Data Scientist / BI Manager and be responsible for the strategic use of data in the company.

The main tasks of this position included:

• Analyzing large data sets to identify patterns and trends,

• Creating predictive models and customer segmentation,

• Optimizing product and pricing strategies,

• Development of business intelligence tools and ETL processes,

• Supporting marketing, sales and IT departments in data-driven activities.

The role had a direct impact on key business indicators, so it was treated as strategic from the start. The person hired for this position was expected to report directly to the board of directors, which emphasized the importance of recruitment for the long-term development of the organization.

2. our approach to recruiting a Data Science expert

Given the strategic importance of the role and the high expectations of the candidate's experience, we began the recruitment process with a thorough understanding of the business context and the expectations of Cyberfolks' management. Already at the recruitment briefing stage, we determined that not only analytical experience would be key, but above all the ability to link data to business objectives - in particular, ARPU optimization and customer segmentation in an e-commerce environment.

Diagnosis of the profile of the ideal candidate

Together with the client, we defined the profile of a person who:

• Has a minimum of 3-5 years of experience in the Data Science or Business Intelligence field,

• Has worked in an e-commerce or similar environment (digital products, large volumes of data),

• Can independently build predictive and recommendation models,

• Is familiar with tools such as SQL, Python, Power BI, Tableau or Looker,

• Knows how to communicate recommendations in a way that non-technical stakeholders can understand.

At the same time, we included soft elements: the ability to work in an agile environment, communication skills, and the flexibility to combine analytical and consulting functions.

Sourcing strategy

We decided to combine several paths to reach candidates:

• Direct search among experienced data specialists from e-commerce and technology companies,

• Precise targeting of ads on specialized platforms, with an emphasis on the strategic dimension of the role,

• interviews with passive candidates who were not actively looking for a job, but met key criteria.

At this stage, we focused on analyzing the candidates' track record - not only the tools they used, but also the impact their actions had on business development. Our emphasis was on those who were able to measure and report on the effects of their initiatives, such as increased retention, improved conversions or an increase in the average shopping cart.

3. recruitment process: step-by-step process

The recruitment process was planned as a project with clearly defined stages, performance metrics and constant contact with the decision-making team on the Cyberfolks side. From the beginning, we wanted an agile but precise selection process, so we divided the activities into three phases: sourcing, pre-selection and working with the client in decision sprints.

Stage 1: sourcing and first selection

During the first 14 days, we sourced and vetted a total of 89 candidates, 27 of whom met the basic hard criteria (experience in BI/Data Science, knowledge of analytical tools, working with large volumes of data). From this group, we selected 9 people, whom we invited to in-depth interviews. Each candidate was evaluated in terms of:

• Data analysis and modeling skills in the context of e-commerce,

• Experience working with non-technical teams,

• Willingness to report independently to management,

• approaches to revenue optimization and ARPU analysis.

Stage 2: prequalification and shortlist recommendation

Based on interviews and technical verification (case analysis, code samples, description of solved business problems), we created a shortlist of 3 candidates who best combined technical competence and strategic approach to data.

All recommendations were prepared in a comparative report format, including:

• competency profile,

• soft and technical assessments,

• Potential risks and motivational factors,

• the proposed onboarding path.

Stage 3: working with Cyberfolks and finalization

The Cyberfolks team was very responsive - decisions on candidates were made within a maximum of 48 hours, and the next steps (meetings with the manager and the board of directors) took place within weekly sprints. As a result, the entire process from the start of sourcing to the submission of an offer took only 29 days.

The final candidate was selected unanimously after an interview with the board, during which he presented not only a strong analytical background, but also specific ideas for optimizing pricing strategy and personalizing offers based on behavioral data.

4th Finalist: competencies that made a difference

The selected candidate stood out not only for his strong technological background, but above all for his ability to translate data into concrete business decisions. He had more than 5 years of experience working at the intersection of Data Science and e-commerce, gained in both large organizations and growth-oriented product companies.

Key strengths of the candidate:

• Familiarity with e-commerce realities - the candidate has previously worked on shopping path optimization, customer segmentation, and cohort analysis, which directly fit Cyberfolks' needs.

• Experienced in predictive modeling - built and implemented models to predict customer churn, conversion from campaigns and purchase behavior based on behavioral data.

• Technology proficiency - he was comfortable with SQL and Python environments, had hands-on experience in creating and automating ETL processes, as well as integrating data from multiple sources.

• Ability to collaborate with the business - was able to translate complex analyses into the language of business benefits. In previous roles, he regularly presented analysis results to management teams and participated in strategic planning.

• Experience in BI tools - used Power BI and Tableau to build dashboards for marketing and sales, enabling real-time tracking of KPIs and faster decision-making.

The candidate had already proposed specific improvements in user segmentation and personalization of price offerings - including the use of algorithms with variable price sensitivity based on user behavior - at the interview stage with management. This proactivity and understanding of the client's business goals determined his selection.

5. conclusions and recommendations for companies looking for data experts

Recruiting a BI Manager / Data Scientist for Cyberfolks confirmed that getting the right data expert is not just a matter of technical competence, but more importantly, the ability to connect analytics to business goals. Based on this project, we have identified several key lessons that may be helpful for companies considering similar hires:

1. data in itself does not generate value - it is done by people who can use it

Even the most sophisticated analytical systems won't work if there aren't people behind them who understand the business context and can make specific recommendations. In this case, the candidate's strategic thinking and ability to operate in the language of value, not just code, were key.

2. industry experience matters - especially in e-commerce

Markets where the dynamics of customer behavior and rapid adaptation of marketing activities are crucial require specialists who understand phenomena such as ARPU, retention, cohort analysis and real-time segmentation. It was important to Cyberfolks that the candidate had experience in an e-commerce environment and knew the challenges of the industry.

3. the selection process must go deeper than a resume

During the recruitment process, we focused not only on the candidates' experience, but also on their mindset, communication with the business and ability to work in an agile decision-making environment. Questions about specific implementations, work results and decisions made proved to be crucial in distinguishing the average analyst from a strategic partner.

4. cooperation with the board is a separate competence

In this recruitment, it was important for the candidate to be able to operate in a management environment, understand the mechanisms of decision-making at the strategic level and be able to argue their recommendations in the language of business impact. This is a competency that is worth checking separately, regardless of knowledge of technical tools.

Opinion of the employed Data Scientist

6. does this challenge apply to your company as well?

In a world of increasing competition, big data volumes and higher customer expectations, decisions based on intuition are no longer enough. Companies that want to increase revenues, optimize products and more accurately reach their audiences need data experts who not only analyze, but realistically influence the direction of the organization.

If you are facing a challenge:

• Increase ARPU or customer retention,

• Implementing a strategy to personalize the offer,

• Better use of data in the sales, marketing or product area,

• Or building analytical competence in the team,

- talk to us. As an IT and digital recruitment agency, we specialize in sourcing data experts who operate at the intersection of technology and business. With a proven process and close cooperation with company boards, we effectively support companies in strategic recruitment.

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