9 of 9 NumPy Jobs in the Thames Valley

managing workflows for collecting, cleaning, and storing large volumes of financial data (e.g., price, volume, fundamentals, alternative data), often using tools like Pandas, NumPy, and Dask. Collaborate Across Teams for Deployment, working with researchers, traders, and DevOps teams to integrate Python models into production environments (e.g., through APIs, microservices ...

Word2Vec, TF-IDF, Word Embeddings - Transformers: BERT, ELMo - OpenAI Models: GPT-3.5 Turbo, GPT-4o, GPT-3o Reasoning, text-embedding-ada-002 Libraries & Tools - numpy, pandas, scipy, scikit-learn, tensorflow, keras, nltk, matplotlib, seaborn, plotly Programming Languages - Python, R, C++, C#, Java, Node.js, HTML, SQL Agentic AI - OpenAI Agents ...

recommendations to non-technical stakeholders. Ideal Qualifications: Strong applied data science or analytics experience in business settings. Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills. Experience with data visualization tools (e.g., Tableau, Power BI). Solid understanding of statistical modeling, experimentation, and A/B testing. ...

tier rankings). Strong experience in data science, analytics, or ML-driven research. Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn. Solid knowledge of experiment design, causal inference, and statistical modeling. Familiarity with SQL, distributed data systems, and experiment tracking tools. Excellent communication ...

tier rankings). Strong experience in data science, analytics, or ML-driven research. Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn. Solid knowledge of experiment design, causal inference, and statistical modeling. Familiarity with SQL, distributed data systems, and experiment tracking tools. Excellent communication ...

tier rankings). Strong experience in data science, analytics, or ML-driven research. Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn. Solid knowledge of experiment design, causal inference, and statistical modeling. Familiarity with SQL, distributed data systems, and experiment tracking tools. Excellent communication ...

Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling … some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science ...

urgently seeking a Senior Data Engineer. You will work with actuarial and asset management datasets, building end-to-end data pipelines in Python (Pandas, NumPy), SQL, GCP (BigQuery), DBT, and Databricks. This role focuses on large-scale financial data, automating processes, integrating multiple data sources, and delivering actionable insights … securities, portfolio valuations, or actuarial outputs in investment, reinsurance, or life insurance environments. Python & SQL: Build analytical pipelines and scalable data solutions using Pandas, NumPy, and SQL. Cloud/Tools: Experience with GCP (BigQuery), DBT, and Databricks. Domain Expertise: Prior delivery of projects in investment operations, reinsurance, or actuarial analytics. ...

urgently seeking a Senior Data Engineer. You will work with actuarial and asset management datasets, building end-to-end data pipelines in Python (Pandas, NumPy), SQL, GCP (BigQuery), DBT, and Databricks. This role focuses on large-scale financial data, automating processes, integrating multiple data sources, and delivering actionable insights … securities, portfolio valuations, or actuarial outputs in investment, reinsurance, or life insurance environments. Python & SQL: Build analytical pipelines and scalable data solutions using Pandas, NumPy, and SQL. Cloud/Tools: Experience with GCP (BigQuery), DBT, and Databricks. Domain Expertise: Prior delivery of projects in investment operations, reinsurance, or actuarial analytics. ...