Senior Data Scientist

Job not on LinkedIn

🔥 1 minute ago

🇬🇧 United Kingdom – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 12%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.Why this score:

• Just posted.
• Jobs at this company usually fill in 31 days.
• No salary listed.

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Gamingtec

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2013

🎲 Gambling

🤝 B2B

☁️ SaaS

Gambling • B2B • SaaS

Gamingtec is a B2B iGaming platform provider that offers turnkey and white-label software for online casinos and sportsbooks. The company supplies modular, scalable platform solutions—casino, sportsbook (including an AI-powered sportsbook), affiliate software, and agent management—designed for rapid market entry (6–8 weeks), multi-jurisdiction regulatory compliance, and extensive integrations (game providers, payments, PAM). Gamingtec supports numerous markets and currencies, reports large event coverage (50,000+ monthly live events, 40,000+ monthly pre-match events), and promotes partnerships with payment and anti-fraud providers. It positions itself as a partner to operators seeking to launch or scale online gambling brands.

📋 Description

• Design, build, and evaluate recommendation, personalization, and ranking models • Develop and apply NLP and GenAI techniques, including RAG and prompt-based approaches, for recommendations and agent workflows • Perform data analysis and feature engineering on large, complex, and messy datasets • Build and maintain offline and online evaluation frameworks for model quality, relevance, latency, and business impact • Investigate failure modes and conduct error analysis • Make practical tradeoffs between quality, speed, and complexity • Partner with engineering and platform teams to deploy, monitor, and iterate on production models • Communicate findings and recommendations to technical and non-technical stakeholders • Stay current with recommendation systems, NLP, and GenAI advances and inform the roadmap • Document models, pipelines, and methodologies • Ensure data handling complies with privacy and security regulations such as GDPR and CCPA • Ship measurable improvements to recommendation, personalization, or GenAI-powered features • Establish evaluation frameworks for core models or agent workflows • Turn ambiguous data or product questions into analyses, experiments, and recommendations • Improve metrics such as relevance, engagement, conversion, retention, latency, or cost efficiency

🎯 Requirements

• 4+ years of experience in data science or machine learning, with a strong focus on recommendation systems, personalization, or ranking • Hands-on experience training, evaluating, and deploying models in production, including NLP or GenAI-based approaches • Proficiency in Python • Solid experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn • Experience with data libraries such as Pandas and NumPy • Strong understanding of collaborative filtering, content-based filtering, and ranking • Working knowledge of prompting, retrieval-augmented generation (RAG), fine-tuning, or GenAI system evaluation • Experience with AWS, GCP, or Azure • Experience with modern data infrastructure such as Spark, Snowflake, BigQuery, or Databricks • Familiarity with version control, Docker, Kubernetes, and experiment tracking tools such as MLflow or Weights & Biases • Strong quantitative and analytical skills • Ability to communicate technical work to non-technical stakeholders • Experience with reinforcement learning, multi-armed bandits, vector databases, retrieval infrastructure, agent orchestration frameworks, A/B testing, early-stage startups, publications, talks, or open-source projects is nice to have • Strong overlap with European time zones preferred

🏖️ Benefits

• Flexible remote environment with strong overlap with European time zones preferred • Competitive salary and equity package • Direct access to the founders and real influence over how Whizdom AI builds and evaluates its models • High-ownership role with room to shape recommendation and GenAI systems used by real customers • Opportunity to work across both classic ML and modern GenAI problems • Small team, low bureaucracy, and a lot of room to grow

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