23 of 23 Pandas Jobs in the South East

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 ❯

end data science projects from ideation to delivery, including business scoping and stakeholder management. Strong proficiency in Python (or R), with deep experience using modern data science libraries (e.g., Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Statsmodels). Solid foundation in SQL and data wrangling across large, complex datasets. Hands-on experience with experimentation platforms, data visualization, and dashboarding tools (e.g. 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 ❯

learning fundamentals, and experimental design. Experience with predictive modeling techniques such as regression, classification, clustering, or time-series forecasting. Proficiency in Python and experience with data science libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost, PyTorch, TensorFlow). Strong experience with SQL and data manipulation across large datasets. Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Plotly, Tableau, or Power BI 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 ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

Stakeholder Communication: Present insights to data labeling experts and technical teams Required Qualifications Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets AI/ML Familiarity: Understanding of LLM More ❯

master’s degree in a STEM subject (Mathematics, Computer Science or Engineering) Experience working in a data science or consulting role In-depth experience of working with Python and Pandas An entrepreneurial spirit and drive to work in an early stage start-up A curious mindset to understand how we can improve things and better help our clients address commercial More ❯

always work with our data, so you will need to understand how to develop your own models Strong programming skills and experience working with Python, scikit-learn, SciPy, NumPy, Pandas and Jupyter Previous experience in finance is not required, although an interest in finance and the motivation to rapidly learn more is a prerequisite for working here. Why should you More ❯

similar fields). Ability to understand business context and translate data into actionable insights that guide decisions. Understanding of experimental design. Proficiency with data manipulation and modelling tools, e.g. pandas, statsmodels, R. Ability to take ownership of tasks and drive projects forward, developing towards end-to-end responsibility. Ability to communicate clearly in writing and speech, adapting technical detail to More ❯

proofs-of-concept , model monitoring , and adoption of emerging AI tech. What We’re Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving skills. Passion for innovation More ❯

or similar role focused on Python coding. It is essential to have good knowledge of Python built in data types/functionality as well as associated tools such as Pandas/Polars, and web frameworks. The ideal candidate will be passionate about the latest AI/Machine Learning/Automation techniques and tools, with some exposure to web scraping tools More ❯

or similar role focused on Python coding. It is essential to have good knowledge of Python built in data types/functionality as well as associated tools such as Pandas/Polars, and web frameworks. The ideal candidate will be passionate about the latest AI/Machine Learning/Automation techniques and tools, with some exposure to web scraping tools More ❯

users Present findings and recommendations to non-technical stakeholders 3. Ideal Qualifications 5+ years of 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 Strong communication skills for More ❯

key strategic initiatives, including price, volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another product-heavy industry. Strong knowledge 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 ❯

model performance. What We're Looking For A Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or a related field. Strong experience with Python and data science libraries (Pandas, Scikit-learn, etc.). Solid understanding of machine learning concepts and algorithms . Interest in working with real-world industrial or sensor data . Exposure to Apache Airflow and/ 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 ❯

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford/Remote (UK) (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 deep-tech company that's … model could change an industry, you'll fit right in. Company Noir Qualifications Senior (5+ years of experience) Experience with 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. Benefits Competitive salary with annual performance based bonuses Equity options - share More ❯

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford/Remote (UK) (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 deep-tech company that's … seeking Machine Learning Engineers with experience in 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, and engineering to More ❯

Adjust, and other MMPs Engineer features for ML models: temporal patterns, user behaviour sequences, campaign attribution Ensure data quality through comprehensive validation, deduplication, schema checks, and defensive programming Optimise pandas/Polars pipelines for performance - we process millions of events daily Handle messy real-world data: duplicates, out-of-order events, schema drift, missing fields, null handling Infrastructure & Orchestration Build … with data scientists to productionise ML workflows and model inference Requirements The ideal candidate must have... 4-6+ years building production data pipelines with demonstrable business impact Deep pandas expertise: you've built real ETL pipelines in production, understand vectorization, memory optimization, and performance patterns Deep expertise in Python and SQL with high code quality standards (e.g. ruff, mypy More ❯

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship More ❯