1 to 25 of 122 Pandas Jobs

quantitative modelling bridging the gap between data and lived football judgement Essential Requirements Technical Skills Advanced proficiency in Python and the data science stack (pandas/polars, scikit-learn, NumPy, matplotlib/plotly) Strong SQL skills ability to design schemas, write complex queries, and manage relational data across large datasets ...

Experience setting up CI/CD pipelines Understanding of service deployment, monitoring, and troubleshooting Data Science/Analytics Experience with data analysis using Python (pandas, numpy) Understanding of data pipelines and ETL processes AI/LLM Engineering Experience integrating LLM APIs (OpenAI, Anthropic, Gemini, or open-source equivalents) into production ...

developers and quantitative teams on new analytics capabilities Participate in debugging, testing, and production support activities Technology Environment Python Databricks/Apache Spark SQL Pandas/NumPy Git REST APIs Cloud technologies (Azure or AWS) Numerix (or equivalent pricing/risk platform) Jupyter/notebook-based analytics workflows Requirements ...

Experience setting up CI/CD pipelines Understanding of service deployment, monitoring, and troubleshooting Data Science/Analytics Experience with data analysis using Python (pandas, numpy) Understanding of data pipelines and ETL processes AI/LLM Engineering Experience integrating LLM APIs (OpenAI, Anthropic, Gemini, or open-source equivalents) into production ...

value What We’re Looking For Essential experience Significant experience building, training and deploying machine learning models Strong Python skills with experience using NumPy, Pandas, SciPy and modern ML frameworks such as PyTorch or TensorFlow Experience working with large-scale unstructured data Experience building and deploying production-ready NLP systems ...

languages such as Python, R, or SQL, and experience with various data science and machine learning libraries. Experience with libraries/frameworks like NumPy, Pandas, SciPy, Scikit‐learn, TensorFlow, PyTorch, Transformers, Langchain, Streamlit, or Gradio, among others. Experience with cloud‐based tools for production use (e.g., AWS SageMaker, AWS Bedrock ...

They're Looking For Around 3-5 years' experience in a Data Science or advanced analytics role Strong Python skills, including libraries such as pandas, NumPy, SciPy, and scikit-learn Experience with gradient boosting frameworks (e.g. LightGBM or similar) Solid grounding in statistics and machine learning concepts Comfortable working with ...

optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing ...

development workflows Comfortable taking ownership and contributing to technical decision making Desirable Skills Experience building SaaS platforms Experience with data science libraries such as pandas, NumPy or scikit-learn Cloud experience across AWS, Azure or GCP Infrastructure as Code tools such as Terraform or CloudFormation Experience with Docker or containerisation ...

environments Strong analytical and problem-solving skills Excellent communication and stakeholder engagement skills Technology Stack Python, SQL, Databricks, PyTorch, Transformers/LLMs, Prompt Engineering, Pandas, Spark, AWS, Azure, PostgreSQL, FastAPI, Git, CI/CD, Knowledge Graphs What's on Offer Fully remote UK-based role Opportunity to work on cutting ...

experience in Data Engineering or a similar technical discipline Strong Python skills with production-level engineering experience Experience with tools/frameworks such as pandas, Polars, DBT Strong understanding of data warehousing, dimensional modelling and medallion architecture Hands-on experience with cloud platforms: AWS, Azure or GCP Experience with orchestration ...

MLOps: Establish CI/CD pipelines and manage model deployment using Kubernetes/OpenShift and MLOps principles. Technical Requirements Core Programming: Expert-level Python (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow, FastAPI, LangChain, LlamaIndex). Generative AI: Deep experience with LLMs (Gemini, OpenAI, Claude, Llama) and evaluating model safety/ ...

scikit-image, PIL) and classical CV algorithms (edge detection, thresholding, color spaces). Data Analytics Fluency: Experience working with standard data manipulation libraries (NumPy, pandas, scikit-learn, SciPy). Communication: Advanced English proficiency to collaborate effectively in a global environment. Bonus Points (Nice to Have) Hands-on experience with Vision ...

entity resolution. GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

Data Engineering, Computer Science, or similar Experience working in commodities, energy trading, or financial markets environments Advanced Python skills, including extensive use of Pandas Experience with analytical or time-series databases (e.g. Redshift, ClickHouse) Hands-on experience with Docker and containerised workloads Experience with Git and modern DevOps practices Practical ...

Python and familiarity with common AI/ML libraries (scikit-learn, PyTorch, HuggingFace, OpenAI API). Bonus Points Experience with data engineering tools (SQL, pandas, dbt, Airflow). Exposure to LLMs or generative AI in a practical context. GitHub profile demonstrating collaborative projects and consistent contributions. Who we are: Here ...

time‐series databases, visualization tools). Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree‐based models, neural networks; MLOps, model deployment, automated testing. Data ...

Experience Required Senior-level experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science ...

efficiency. Contributing to a culture of knowledge-sharing and continuous improvement. Key Skills & Experience Strong Python skills and familiarity with ML libraries such as Pandas, NumPy, and scikit-learn. Experience with frameworks such as TensorFlow, Keras, or PyTorch. Exposure to gradient boosting tools such as XGBoost, LightGBM, or CatBoost. Experience ...

models that perform reliably in complex operational environments. What We’re Looking For Strong experience in Python and SQL, including libraries such as Pandas, NumPy and scikit-learn. Experience working with deep learning frameworks such as PyTorch or TensorFlow. A solid grounding in statistics and probability, with strong mathematical foundations ...

Deep understanding of object-oriented design, concurrency, and high-performance distributed systems Proficient in Python; Including use of libraries such as NumPy, SciPy and Pandas for quantitative analysis and prototyping Proven experience applying numerical optimisation techniques and/or machine learning methods to pricing, trading or market-related problems Prior ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...