20 of 20 SciPy Jobs in the UK

concise documentation and analysis. NICE TO HAVE BUT NOT ESSENTIAL Proficient in python’s various data transformation, visualisation and statistics libraries i.e. pandas, numpy , scipy and plotly Experience leading a team or owning a whole product domain PROCESS 1) Screening call with recruiter - 30 mins 2) Take home Case Study ...

ensemble methods. Familiarity with rigorous experimentation: online/offline evaluation, data leakage prevention, and model governance. Tech Stack Python, SQL, pandas/numpy/scipy, PyTorch/sklearn Airflow/dbt, Kafka (or equivalents), Postgres/BigQuery Docker, Kubernetes (optional), CI/CD (GitHub Actions) Observability: Prometheus/Grafana, OpenTelemetry ...

modern MLOps tooling (e.g. MLflow, Weights & Biases, DVC, Airflow) Strong experience with Python and associated scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit-learn, etc. Strong software engineering practices including version control, code review, software testing methodologies, and continuous integration; experience with IEC 62304 is particularly desirable ...

data engineering, analytics, and data science. Proficiency in Python (Airflow, Pandas, NumPy) is essential for both data science and data engineering tasks. TensorFlow, SciPy, PySpark, Matplotlib, Seaborn experience is a significant plus. Data Modeling Expertise - A strong understanding of dimensional modeling, star, snowflake schemas, and relationship structures, ensuring efficient ...

Quantitative Finance, Mathematics, Physics, Engineering, Computer Science, or a related STEM discipline Strong understanding of data fundamentals and their python implementations (numpy, polars, scipy) Strong knowledge of AI/ML techniques with experience delivering related work into production Curious to explore how AI can improve how we build, deliver ...

leading the delivery of data science or AI projects from concept to production. Strong knowledge of Python and core ML libraries (e.g., spaCy, NumPy, SciPy, Transformers). Understanding of big data and cloud technologies (Spark, Hadoop, Azure, AWS, or GCP). Deep expertise in MLOps principles, scalable model deployment ...

leading the delivery of data science or AI projects from concept to production. Strong knowledge of Python and core ML libraries (e.g., spaCy, NumPy, SciPy, Transformers). Understanding of big data and cloud technologies (Spark, Hadoop, Azure, AWS, or GCP). Deep expertise in MLOps principles, scalable model deployment, model ...

verbal) Risk and control-oriented mindset: ability to ask incisive questions, assess materiality of model issues, and escalation issues appropriately. Proficiency in Python (NumPy, SciPy, Pandas, etc). Curious, ownership-driven, and teamwork-oriented mindset. Preferred qualifications, capabilities and skills Prior model validation or front-office quant experience in pricing ...

architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining ...

architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining ...

environmental data analysis. Excellent analytical skills with the ability to interpret complex real-world datasets. Strong Python skills for scientific analysis (NumPy, Pandas, SciPy or similar). Experience communicating technical findings to both technical and non-technical audiences. Ability to work collaboratively across software, engineering and scientific teams. Desirable Experience ...

systems. Experience using distributed computing frameworks such as Ray and managing GPU workloads across multiple nodes. Knowledge of platforms and tools such as PyTorch, SciPy, scikit-learn, NumPy, pandas, MLflow, Docker, Kubernetes, and cloud infrastructure. Understanding of industrial systems, including heating, cooling, manufacturing, or data center environments. Scientific or technical ...

factual grounding. Technical Proficiency Machine learning algorithms: linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks Data science tools: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras Cloud computing platforms: AWS, Azure, GCP Natural language processing: transformer models, attention mechanisms, word embeddings Computer vision: convolutional neural networks, recurrent ...

Exposure to recommendation algorithms, NLP, or People Analytics is a major plus. Python Mastery: Fluent in Python and specialized machine learning libraries (scikit-learn, SciPy, statsmodels). Experience with NLP frameworks (spaCy, HuggingFace, or text embeddings) is highly valued. Statistical Rigor: Solid foundation in applied statistics, including clustering, predictive modeling ...

Exposure to recommendation algorithms, NLP, or People Analytics is a major plus. Python Mastery: Fluent in Python and specialized machine learning libraries (scikit-learn, SciPy, statsmodels). Experience with NLP frameworks (spaCy, HuggingFace, or text embeddings) is highly valued. Statistical Rigor: Solid foundation in applied statistics, including clustering, predictive modeling ...

STEM discipline Proven experience delivering data science, machine learning or AI solutions in a commercial environment Strong programming capability in Python (Pandas, NumPy, SciPy or similar) Solid grounding in statistics, probability and data analysis AI & LLM Experience Hands-on experience with large language models, including: RAG pipelines Fine-tuning approaches ...

machine learning techniques such as regularised regression, clustering or tree-based ensembles (and experience applying them with packages like Pandas, sci-kit-learn, SciPy) is highly beneficial Experience processing big data, ideally in a Hadoop/Spark environment, would be beneficial Proven experience implementing CI/CD and DevOps practices ...

machine learning techniques such as regularised regression, clustering or tree-based ensembles (and experience applying them with packages like Pandas, sci-kit-learn, SciPy) is highly beneficial Experience processing big data, ideally in a Hadoop/Spark environment, would be beneficial Proven experience implementing CI/CD and DevOps practices ...

structured, or unstructured data, especially large-scale text or content datasets. Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib. The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem ...

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Research Scientist (Model-based RL) based inUnited Kingdom. This role ...