1 to 25 of 26 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 ❯

to undertake a contract assignment. In order to be successful, you will have the following experience: Extensive AI & Data Development background Experiences with Python (including data libraries such as Pandas, NumPy, and PySpark) and Apache Spark (PySpark preferred) Strong experience with data management and processing pipelines Algorithm development and knowledge of graphs will be beneficial SC Clearance is essential Within More ❯

experienced AI/Data Developer for an urgent contract assignment. Key Requirements: Proven background in AI and data development Strong proficiency in Python , including data-focused libraries such as Pandas, NumPy, and PySpark Hands-on experience with Apache Spark (PySpark preferred) Solid understanding of data management and processing pipelines Experience in algorithm development and graph data structures is advantageous Active More ❯

ML models in a financial services environment (Banking, FinTech, Insurance, or related). Technical Skills: Programming: Expert proficiency in Python (must-have) and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn). Proficiency in SQL is essential. Machine Learning: Deep, hands-on experience with a wide range of ML techniques (supervised/unsupervised learning, time-series analysis, ensemble 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 ❯

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 ❯

Description:- Data Engineer (Python enterprise developer): 6+ years of experience in python scripting. Proficient in developing applications in Python language. Exposed to python-oriented Algorithms libraries such as NumPy, pandas, beautiful soup, Selenium, pdfplumber, Requests etc. Proficient in SQL programming, Postgres SQL. Knowledge on DevOps like CI/CD, Jenkins, Git. Experience working with AWS(S3) and Azure Databricks. Have 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 ❯

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 ❯

and innovation within the team. 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 ❯

and innovation within the team. 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 ❯

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 ❯

version control processes. Stay up to date with advances in quantitative finance, computational techniques, and emerging technologies. Profile Strong programming experience in Python, C++, or C#; knowledge of NumPy, Pandas, and QuantLib advantageous. Solid understanding of mathematics, statistics, and numerical methods - including stochastic calculus, Monte Carlo simulation, and optimisation. Familiarity with derivatives pricing, risk metrics, and financial instruments across asset More ❯

standards for security, accessibility, and performance. Key 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 ❯

large, complex datasets. Desirable Experience & Skills Practical knowledge of data engineering practices (designing and building robust data pipelines) Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel More ❯

AI models. Collaborate with data scientists, software engineers, and subject-matter experts to deliver innovative solutions. Essential Skills & Experience Advanced Python programming skills with hands-on experience using NumPy, Pandas, Scikit-learn, Langchain, LlamaIndex , and Azure AI Foundry . Proven experience working with Azure cloud services and Generative AI R&D. Strong understanding of machine learning, data modelling , and natural 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 ❯

predictive model- Clear explainability on what drives user clicks- A functional internal tool for non-technical stakeholders- Documentation and guidance for productionisation Required Skills Must-Have: Expert-level Python (Pandas, modelling libraries such as Scikit-learn) SQL AWS cloud experience Proven end-to-end ownership of data science solutions Model explainability (SHAP, LIME, feature importance) Ability to build simple dashboards More ❯

Experience: Proven experience working as a Data Scientist or Machine Learning Engineer in a commercial setting. Strong programming skills in Python, with hands-on experience using libraries such as Pandas, Scikit-Learn, Jupyter, and Matplotlib. Proficient in SQL for data extraction and transformation. Experience with Google Cloud Platform (GCP) and Vertex AI for developing and deploying ML services is highly More ❯

and T&L domain experts Required Skills/Experience The ideal candidate will have the following: Be an expert Python programmer proficient in frameworks/libraries such as: Numpy, Pandas, Scikit-Learn, Langchain, Llamaindex, Azure AI Foundry amongst others. Must have Azure and be an expert with R&D on generative AI techniques Practical experience with GenAI techniques such as 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 ❯

. Utilise SQL for data extraction, transformation, and analysis. Skills & Experience Proven experience working as a Pricing Analyst. Strong proficiency in SQL and Python (including data libraries such as pandas, NumPy, scikit-learn, etc.) Skilled in Power BI or equivalent visualisation platforms. Background in retail, ticketing, or loyalty environments preferred. Experience in clustering, segmentation, and data modelling. Location: Shepherds Bush 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 ❯

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 ❯

data analysis and validation. Analyse all datasets to ensure that each KPI is understood, and data is ready for modelling. Proficiency in using Excel/SQL/Python/Pandas to process, transform, create variables, and build models. Build base models according to the project specification, incorporating all drivers of KPIs, providing rationale for variables selection, understanding coefficients and contributions. More ❯