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  • Lead Data Scientist
    Data

    Lead Data Scientist

    Londyn
    Type of work
    Full-time
    Experience
    Senior
    Employment Type
    Any
    Operating mode
    Remote

    Tech stack

      Data Science

      master

      Machine Learning

      advanced

      AWS

      advanced

      PyTorch

      advanced

      Spark

      advanced

      Hadoop

      advanced

      TensorFlow

      advanced

      SQL

      advanced

      Python

      advanced

      Scala

      advanced

    Job description

    Online interview
    Friendly offer

    Role Overview:

    As the Lead 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 behavior 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.


    The company guarantees you the following benefits:

    • 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.


    Interview process:

    • A 1-hour interview with the Co-Founder to get to know you and your experience;
    • A 1-hour technical interview to check your hard skills;
    • A test task;
    • A final 30-minute-long interview to talk about your implementation of the test task.



    If you find this opportunity right for you, don't hesitate to apply or get in touch with us if you have any questions!


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