19 of 19 Contract Pandas Jobs

and more on reliability and fixes. Key Skills: Investigating and debugging complex data flow and Machine Learning issues within a live, high impact production environment. Extensive Python, NumPy and Pandas is required for this role. You must demonstrate a deep commercial background in the following areas: Extensive Python: Very strong, production-level Python coding and debugging skills. Production Environment: Proven More ❯

matter expert for pricing models and valuation logic, supporting risk and trading teams globally. Skills and Experience Expert-level Python developer with strong experience in numerical computing (NumPy, SciPy, Pandas). Deep understanding of derivatives pricing theory, volatility modelling, and stochastic calculus. Experience with calibration, curve bootstrapping, and risk measures (Greeks, sensitivities, VaR). Background in pricing and risk models More ❯

continuous improvement initiatives Essential Skills for the AWS Data Engineer: Extensive hands-on experience with AWS data services Strong programming skills in Python (including libraries such as PySpark or Pandas) Solid understanding of data modelling, warehousing and architecture design within cloud environments Experience building and managing ETL/ELT workflows and data pipelines at scale Proficiency with SQL and working More ❯

is required for this role. Essential Skills & Experience: • Proven experience developing solutions with Power Apps (Canvas and Model-driven apps). • Strong proficiency in Python, including libraries such as Pandas, NumPy, and Flask or FastAPI. • Experience with Microsoft Power Platform, including Power Automate and Dataverse. • Ability to mentor and support junior staff in technical development. • Excellent communication and stakeholder engagement More ❯

learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP/Azure, Docker, Kubernetes, MLflow More ❯

flows and ML issues in live production environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer More ❯

visualisation libraries (Matplotlib, Seaborn.) SQL for data extraction and manipulation. Experience working with large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for More ❯

Hands-on programming experience Proficient Python Programming Functions, classes & object-oriented programming List comprehensions & generators Error handling Working with virtual environments & package management (pip, venv) Data Manipulation & Analysis Libraries: pandas, numpy (optional: polars) Data cleaning & preprocessing Handling missing values Grouping, merging, pivoting & aggregations SQL knowledge Software Engineering Best Practices Version control using Git Writing modular & reusable code Unit testing (e.g. More ❯

up-to-date with emerging trends and technologies in the field of data science. Requirements Proven experience as a data scientist using Python and a range of libraries (Numpy, Pandas, Scikit-Learn, Matplotlib, Plotly etc.). Strong expertise in statistical modelling, machine learning, and data mining techniques. Data engineering (pipelines, databases, infrastructure), ideally with AWS experience would be an advantage. More ❯

Stay informed on emerging trends, technologies, and best practices in data science. Experience Required: Proven experience as a Data Scientist with proficiency in Python and libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, and Plotly. Strong background in statistical modelling, machine learning, and data mining, with experience working on time-series data. Knowledge of data engineering principles, including pipelines, databases More ❯

or related pricing/trading systems Solid understanding of algorithms, data structures, and design patterns Experience with relational and NoSQL databases (PostgreSQL, Redis, MongoDB) Proficiency in data processing using pandas, NumPy , and working with APIs Understanding of CI/CD pipelines and DevOps practices Preferred: Quantitative analysis, financial modeling, or experience with trading systems Familiarity with distributed systems and event More ❯

or related pricing/trading systems Solid understanding of algorithms, data structures, and design patterns Experience with relational and NoSQL databases (PostgreSQL, Redis, MongoDB) Proficiency in data processing using pandas, NumPy , and working with APIs Understanding of CI/CD pipelines and DevOps practices Preferred: Quantitative analysis, financial modeling, or experience with trading systems Familiarity with distributed systems and event More ❯

LangGraph, MCP, Google ADK or similar Build solutions for LLM fine-tuning, RAG, and multi-agent AI workflows. Build Python based solutions using key data science and ML libraries (Pandas, NumPy, Scikit-learn, PyTorch, Hugging Face, etc ) Prepare documentation and sharing solution designs, decisions, and results with both technical and non-technical audiences. Required experience: Strong Python skills PyTorch, Hugging More ❯

of-concepts and assist the business with evaluations to measure success and estimate value proposition. Essential Criteria: * Extensive experience with Python and data science Python packages (e.g. scikit-learn, pandas, numpy, etc) * Understanding of data science concepts, AI/ML models, evaluation approaches, and data science applications to enhance business processes * Proven hands-on experience in Microsoft Azure ML Studio More ❯

experience as a Data Scientist , ideally in a government or large-scale enterprise environment. Strong Python programming skills, including experience with data science and AI/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI More ❯

experience as a Data Scientist , ideally in a government or large-scale enterprise environment. Strong Python programming skills, including experience with data science and AI/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI More ❯

experiments for LLM fine-tuning, retrieval-augmented generation (RAG), and multi-agent AI workflows . Deliver production-grade Python code using advanced data science, ML, and analytics libraries (eg, Pandas, NumPy, Scikit-learn, PyTorch, Hugging Face Transformers, Pydantic ). Document and communicate AI designs, decisions, and experiment outcomes to both technical and non-technical stakeholders. Lead the design and deployment More ❯

an umbrella company for the duration of the contract. You must have several years of experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc. You will also have a number of years hands-on experience with cloud services, especially Databricks, for building and managing scalable data pipelines. ETL process expertise is More ❯

AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using More ❯