Senior Data Scientist

As a Data Scientist, you'll have the unique opportunity to shape the future of recommendation systems and make a significant impact on a dynamic startup.
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Remote Kyiv London Limassol Tbilisi

Are you ready to bring your Data Science experience to the next level?

As the Senior Data Scientist, you will be responsible for enhancing our recommendation systems and leading the data science team. You will work closely with cross-functional teams to develop, implement, and optimize machine learning models that drive our core product offerings. Your role will also involve building and managing a team of data scientists and researchers, ensuring that our projects are executed efficiently and effectively.

Key Responsibilities:

1. Model Development and Optimization:

  • Design, develop, and implement state-of-the-art recommendation algorithms;
  • Optimize existing models to improve accuracy, scalability, and performance;
  • Collaborate with engineering teams to integrate models into production systems.

2. Team Leadership and Management:

  • Recruit, train, and mentor a team of data scientists and researchers;
  • Provide technical guidance and oversight to ensure high-quality deliverables;
  • Foster a collaborative and innovative team culture.

3. Data Analysis and Insights:

  • Conduct deep-dive analyses to understand user behaviour and improve recommendation accuracy;
  • Develop and maintain data pipelines and ETL processes;
  • Create dashboards and reports to communicate findings and recommendations to stakeholders.

4. Research and Innovation:

  • Stay abreast of the latest developments in AI/ML and recommendation systems;
  • Drive innovation by exploring new techniques and technologies;
  • Publish and present research findings at industry conferences and workshops.

5. Stakeholder Collaboration:

  • Work closely with product managers, engineers, and other stakeholders to align data science initiatives with business goals;
  • Translate complex technical concepts into clear, actionable insights for non-technical audiences.

Qualifications and Skills:

1. Education:

  • Master’s or Ph.D. in Computer Science, Data Science, Statistics, or a related field.

2. Experience:

  • 5+ years of experience in data science, with a focus on machine learning and recommendation systems;
  • Proven track record of developing and deploying large-scale recommendation models;
  • 2+ years of experience in a leadership or managerial role, with a history of building and managing high-performing teams.

3. Technical Skills:

  • Proficiency in programming languages such as Python or Scala;
  • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn);
  • Strong understanding of data processing tools and platforms (e.g., Hadoop, Spark, SQL);
  • Must have experience with AWS cloud services (e.g., S3, EC2, SageMaker, Redshift);
  • Familiarity with other cloud computing platforms (e.g., GCP, Azure) is a plus.

4. Soft Skills:

  • Excellent problem-solving and analytical skills;
  • Strong communication and presentation abilities;
  • Ability to work effectively in a fast-paced, startup environment.


  • Competitive salary and equity package;
  • Flexible working hours and remote work options;
  • Opportunity to work on cutting-edge technologies and shape the future of AI/ML recommendations;
  • A collaborative and inclusive company culture;
  • Professional development opportunities and support for continuous learning.

Sounds interesting? Do not hesitate to apply or contact us if you have any questions!

Advantages of Our Company

Zero bureaucracy

Unlimited holidays

Medical insurance

Only top talent and top salaries

Challenging projects and tasks

Smartest colleagues in the industry

Our Principles

Celebrate diversity

Celebrate diversity

Innovation matters

Innovation matters

Ambitious goals

Ambitious goals

Get in touch

If you are interested in finding out more about our offering, please complete the form below and a member of our team will be in touch shortly.

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