826 to 850 of 1,112 Permanent Pandas Jobs

such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science More ❯

learning applications such as recommendation systems, segmentation, and marketing optimisation. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in Jupyter notebooks, Pandas, and PyTorch. Familiarity with cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong problem-solving skills and a passion for driving measurable More ❯

of transfer learning and popular augmentation techniques Able to apply machine learning to real-life problems Vision Transformers, DeepLabv3, SegFormer, etc.Python, Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras Thrive in a cross-functional working environment Possess a clear passion for data science beyond the day job Nice More ❯

of transfer learning and popular augmentation techniques Able to apply machine learning to real-life problems Vision Transformers, DeepLabv3, SegFormer, etc.Python, Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras Thrive in a cross-functional working environment Possess a clear passion for data science beyond the day job Nice More ❯

learning applications such as recommendation systems, segmentation, and marketing optimisation. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in Jupyter notebooks, Pandas, and PyTorch. Familiarity with cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong problem-solving skills and a passion for driving measurable More ❯

mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or More ❯

mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or More ❯

mindset. Proven track record with NLP applications and transformer-based models like BERT or GPT. Advanced proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or More ❯

run better. What you’ll do Interrogate large datasets in SQL to analyse depot efficiency, delivery timelines, stock levels, and service bottlenecks Use Python (Pandas, NumPy, scikit-learn/statsmodels) to apply performance models or forecasting where needed Build and maintain some Power BI dashboards — but you won’t be More ❯

run better. What you’ll do Interrogate large datasets in SQL to analyse depot efficiency, delivery timelines, stock levels, and service bottlenecks Use Python (Pandas, NumPy, scikit-learn/statsmodels) to apply performance models or forecasting where needed Build and maintain some Power BI dashboards — but you won’t be More ❯

run better. What you’ll do Interrogate large datasets in SQL to analyse depot efficiency, delivery timelines, stock levels, and service bottlenecks Use Python (Pandas, NumPy, scikit-learn/statsmodels) to apply performance models or forecasting where needed Build and maintain some Power BI dashboards — but you won’t be More ❯

run better. What you’ll do Interrogate large datasets in SQL to analyse depot efficiency, delivery timelines, stock levels, and service bottlenecks Use Python (Pandas, NumPy, scikit-learn/statsmodels) to apply performance models or forecasting where needed Build and maintain some Power BI dashboards — but you won’t be More ❯

track record of delivering impactful projects. Strong statistical and machine learning expertise, with the ability to apply and evaluate various algorithms. Proficiency in Python (Pandas), SQL, and data analytics tools. Experience deploying and evaluating ML models in production environments. Ability to interpret complex datasets, drawing meaningful insights to drive business More ❯

track record of delivering impactful projects. Strong statistical and machine learning expertise, with the ability to apply and evaluate various algorithms. Proficiency in Python (Pandas), SQL, and data analytics tools. Experience deploying and evaluating ML models in production environments. Ability to interpret complex datasets, drawing meaningful insights to drive business More ❯

as a Data Scientist or in a similar analytical role. Strong programming skills in Python or R, with proficiency in data manipulation libraries (e.g., Pandas, NumPy). Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib). Solid understanding of statistics, probability, and More ❯

to the founding members, and you’ll be given ownership on the direction of data engineering across the business. They’re currently using Python (Pandas), PostgreSQL, on AWS as the core technologies within data engineering, but you’ll also work on some exciting AI projects. If you feel there’s More ❯

concepts, data modeling techniques, and data mining principles. Proficiency in programming languages such as Python or R, and experience with data science libraries (e.g., Pandas, Scikit-learn, TensorFlow). Experience with data visualization tools such as Tableau or Power BI. Familiarity with Agile methodologies and MBSE principles is a plus. More ❯

to the founding members, and you’ll be given ownership on the direction of data engineering across the business. They’re currently using Python (Pandas), PostgreSQL, on AWS as the core technologies within data engineering, but you’ll also work on some exciting AI projects. If you feel there’s More ❯

to the founding members, and you’ll be given ownership on the direction of data engineering across the business. They’re currently using Python (Pandas), PostgreSQL, on AWS as the core technologies within data engineering, but you’ll also work on some exciting AI projects. If you feel there’s More ❯

experience in translating technical methods to non-technical stakeholders Strong programming experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain) Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival More ❯

or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or Engineering - or equivalent. Proficiency in Python and relevant data science libraries (NumPy, pandas, scikit-learn, etc.). Experience with SQL, Power BI, Git & GitHub. Strong knowledge of Machine Learning Algorithms and respective theory. Ability to work within a More ❯

development Strong programming skills in Python and experience with production grade python code Deep knowledge of Python libraries such as Scikit-learn, PySpark, NumPy, Pandas Familiarity with Python's unit testing framework (currently using pytest) Experience collaborating and using Github Excellent communication and teamwork skills, with a strong attention to More ❯

of experience as a Data Analyst or Data Scientist in IT companies. Proficiency in SQL (BigQuery experience is a plus). Solid Python knowledge (pandas, numpy at least intermediate level). Strong knowledge of statistics and probability theory. Experience with A/B testing analysis. Experience building analytical models. Understanding More ❯

improvements through DevOps and Infrastructure-as-Code (ideally using Terraform) Take ownership of system observability, stability, and documentation Requirements Strong experience in Python (especially Pandas and PySpark) and SQL Proven expertise in building data pipelines and working with Databricks and Lakehouse environments Deep understanding of Azure (or similar cloud platforms More ❯

an agentic analysis solution capable of performing multi-step financial analysis and processing, including data querying, variance analysis, data quality analysis, and Python/Pandas code generation and execution. Enable the chatbot to request and pull data, perform calculations, and create visual representations like pie charts to demonstrate data effectively. More ❯