Data Science Lead

2 weeks ago

London, Greater London, United Kingdom DataTech Analytics Full time

Data Science Lead Opportunity


We are seeking a talented Data Science Lead to join our DataTech Analytics team in London. In this role, you will be responsible for delivering valuable insights to our clients through innovative analytics.


Key Responsibilities:



  • Provide data analytics and data science services that generate meaningful insights, helping clients understand their business risks and key drivers using tools such as Python, R, Azure, Databricks, SQL, Tableau, and Power BI.
  • Review and enhance both internal and third-party data science and cloud solutions.
  • Develop and implement innovative data science and machine learning tools to meet the evolving needs of the organisation.
  • Collaborate with clients in managing large datasets through effective handling, manipulation, analysis, and modeling.

Essential Skills:



  • Strong problem-solving abilities.
  • Proficiency in Python, including libraries such as pandas, numpy, and scikit.
  • Solid understanding of the mathematical, probability, and statistical principles behind machine learning models.
  • Experience with deploying common machine learning algorithms (both supervised and unsupervised).
  • Excellent communication and data presentation skills, with the ability to share technical concepts in an accessible way for all audiences.
  • End-to-end experience on at least one data science project, including data wrangling, feature engineering, model training, and validation.
  • Self-motivated and capable of working independently while also thriving in a team environment.
  • Ability to apply data science principles with a business-focused perspective.

Desirable Skills:



  • Experience using R.
  • Familiarity with deep learning techniques (RNNs, CNNs) and NLP methods (TF-IDF, word embeddings).
  • Understanding of Large Language Models, generative AI frameworks, prompt engineering, and fine-tuning.
  • Knowledge of software engineering best practices, including test-driven development and effective data structures.
  • Experience with cloud environments (Azure, AWS) and tools like Azure Databricks, MLflow, and ML services.
  • Familiarity with Dev/MLOps environments and tools such as Git, Docker, and Kubernetes.
  • Experience in Agile development teams.
  • Front-end development experience (React, Django) is a plus.
  • Background in delivering data science and machine learning projects within the financial industry or complex organisations.

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