analytics platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit youll use Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD More ❯
City of London, Greater London, UK Hybrid / WFH Options
Areti Group | B Corp
analytics platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit youll use Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/CD More ❯
Terraform for provisioning data infrastructure, including permissions, clusters, jobs, and lakehouse resources. Proven experience in building MLOps pipelines, tracking model lifecycle, and integrating with modern ML frameworks (e.g., scikit-learn, XGBoost, TensorFlow). Exposure to streaming data pipelines (e.g., Kafka, Structured Streaming) and real-time analytics architectures is a strong plus. Experience implementing robust DevOps practices for data More ❯
Terraform for provisioning data infrastructure, including permissions, clusters, jobs, and lakehouse resources. Proven experience in building MLOps pipelines, tracking model lifecycle, and integrating with modern ML frameworks (e.g., scikit-learn, XGBoost, TensorFlow). Exposure to streaming data pipelines (e.g., Kafka, Structured Streaming) and real-time analytics architectures is a strong plus. Experience implementing robust DevOps practices for data More ❯
City of London, Greater London, UK Hybrid / WFH Options
Aspect
years in AI/ML, with at least 1 year focused on Generative AI and NLP. Strong programming skills in Python; proficient in libraries such as NumPy, Pandas, scikit-learn, PyTorch, TensorFlow. Proven experience building and scaling GenAI applications in production. Expertise in LLM architectures (OpenAI, LLaMA, Mistral, etc.) and RAG implementation. Familiarity with frameworks like LangChain, LlamaIndex More ❯
business outcomes. What Youll Bring Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). Strong leadership in project delivery, architecture, and technical decision-making. Excellent communicator, able to simplify complex ideas for any audience. Strategic More ❯
business outcomes. What Youll Bring Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). Strong leadership in project delivery, architecture, and technical decision-making. Excellent communicator, able to simplify complex ideas for any audience. Strategic More ❯
environment Build scalable data pipelines and APIs Ideal Candidate Will Have: Previous experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and More ❯
environment Build scalable data pipelines and APIs Ideal Candidate Will Have: Previous experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and More ❯
to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large Big Data environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯
Physics, or Engineering Experience building and deploying ML models into production (e.g., in forecasting, optimisation, or computer vision) Proficiency in Python and familiarity with key ML libraries like Scikit-learn, TensorFlow, or PyTorch Solid foundation in statistical modelling and machine learning techniques Exposure to cloud technologies such as AWS, especially services like SageMaker or Lambda, is a bonus More ❯
Physics, or Engineering Experience building and deploying ML models into production (e.g., in forecasting, optimisation, or computer vision) Proficiency in Python and familiarity with key ML libraries like Scikit-learn, TensorFlow, or PyTorch Solid foundation in statistical modelling and machine learning techniques Exposure to cloud technologies such as AWS, especially services like SageMaker or Lambda, is a bonus More ❯
Engineering) is highly preferred Demonstrated ability to deploy production-level ML modelsparticularly in optimisation, demand forecasting, or computer vision Advanced proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch Solid understanding of supervised and unsupervised learning, statistical modelling, and mathematical optimisation Hands-on experience with AWS services, especially SageMaker, Lambda, and related infrastructure Willingness More ❯
Engineering) is highly preferred Demonstrated ability to deploy production-level ML modelsparticularly in optimisation, demand forecasting, or computer vision Advanced proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch Solid understanding of supervised and unsupervised learning, statistical modelling, and mathematical optimisation Hands-on experience with AWS services, especially SageMaker, Lambda, and related infrastructure Willingness More ❯
and deployment hurdles. Ability to translate business questions into analytical frameworks and interpret results for non-technical stakeholders. Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker. Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention. … social media, and paid media. Excellent problem-solving skills, business acumen, and the ability to translate complex models into actionable insights for non-technical stakeholders. Tools/Frameworks : Scikit-learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy … matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake, Databricks, Redshift, BigQuery) Familiarity with data pipelines and orchestration tools like Airflow Work closely with Data Engineers to ensure model-ready data and More ❯
SR2 | Socially Responsible Recruitment | Certified B Corporation
to bring ideas to life What theyre looking for: 13 years experience in applied ML/AI (or equivalent projects) Strong Python skills with PyTorch, Hugging Face or scikit-learn Experience experimenting with LLMs (fine-tuning, embeddings, prompt chaining etc.) A passion for turning messy real-world data into something powerful and production-ready Excitement about being the More ❯
SR2 | Socially Responsible Recruitment | Certified B Corporation
to bring ideas to life What theyre looking for: 13 years experience in applied ML/AI (or equivalent projects) Strong Python skills with PyTorch, Hugging Face or scikit-learn Experience experimenting with LLMs (fine-tuning, embeddings, prompt chaining etc.) A passion for turning messy real-world data into something powerful and production-ready Excitement about being the More ❯
