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Lead Data Scientist

fully flexible
Remote: 
Full Remote
Contract: 
Experience: 
Senior (5-10 years)
Work from: 

Offer summary

Qualifications:

Master’s or Ph.D. in Computer Science, Data Science, Statistics, or related field, 5+ years experience in data science and leadership.

Key responsabilities:

  • Develop and optimize recommendation algorithms
  • Lead data science team and collaborate cross-functionally
  • Conduct data analysis, maintain pipelines, and create reports
  • Stay updated on AI/ML advancements, drive innovation
  • Collaborate with stakeholders to align initiatives with business goals
Gamingtec logo
Gamingtec SME https://gamingtec.com/
51 - 200 Employees
See more Gamingtec offers

Job description

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

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 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.


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.


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

Required profile

Experience

Level of experience: Senior (5-10 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

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