Senior Data Scientist

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Design, construct, and assess models for recommendation, personalization, and ranking.

• Develop and implement NLP and GenAI techniques, including retrieval-augmented generation (RAG) and prompt-based methods, for recommendations and agent workflows.

• Conduct data analysis and feature engineering on extensive, intricate, and unstructured datasets.

• Create and sustain offline and online evaluation frameworks to measure model quality, relevance, latency, and business impact.

• Examine failure modes and perform error analysis.

• Make informed trade-offs between quality, speed, and complexity.

• Collaborate with engineering and platform teams to deploy, monitor, and refine production models.

• Present findings and recommendations to both technical and non-technical stakeholders.

• Keep abreast of developments in recommendation systems, NLP, and GenAI, and contribute to the roadmap.

• Document models, pipelines, and methodologies thoroughly.

• Ensure data management aligns with privacy and security regulations such as GDPR and CCPA.

• Deliver measurable enhancements to features powered by recommendation, personalization, or GenAI.

• Establish evaluation frameworks for foundational models or agent workflows.

• Transform vague data or product inquiries into analyses, experiments, and actionable recommendations.

• Enhance metrics such as relevance, engagement, conversion, retention, latency, or cost efficiency.

⛳️ Requirements

• Over 4 years of experience in data science or machine learning, emphasizing recommendation systems, personalization, or ranking.

• Practical experience in training, evaluating, and deploying models in production, particularly with NLP or GenAI-based methodologies.

• Proficient in Python programming.

• Solid background with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.

• Experience with data libraries like Pandas and NumPy.

• Strong comprehension of collaborative filtering, content-based filtering, and ranking algorithms.

• Familiarity with prompting, retrieval-augmented generation (RAG), fine-tuning, or evaluations of GenAI systems.

• Experience using cloud services like AWS, GCP, or Azure.

• Knowledge of modern data infrastructure tools such as Spark, Snowflake, BigQuery, or Databricks.

• Acquainted with version control systems, Docker, Kubernetes, and experiment tracking tools like MLflow or Weights & Biases.

• Strong quantitative and analytical abilities.

• Capability to convey technical work to non-technical audiences.

• Experience with reinforcement learning, multi-armed bandits, vector databases, retrieval infrastructure, agent orchestration frameworks, A/B testing, early-stage startups, publications, presentations, or open-source contributions is a plus.

• Preference for candidates with significant overlap with European time zones.

🏝️ Benefits

• Flexible remote work environment with a strong preference for overlap with European time zones.

• Competitive salary and equity package.

• Direct access to the founders and substantial influence over the development and evaluation of models at Whizdom AI.

• High-ownership role with opportunities to shape recommendation and GenAI systems utilized by real customers.

• Chance to engage with both traditional ML and contemporary GenAI challenges.

• Small team structure, minimal bureaucracy, and ample opportunities for growth.