1 to 25 of 118 Permanent Pandas Jobs

models What We’re Looking For: Essential Skills & Experience Proven experience solving complex, real-world problems using data science and analytics Strong Python skills (pandas, numpy, scikit-learn) with a solid grounding in probability and statistics Deep understanding of machine learning methods and their practical applicati on.Experience delivering multiple ...

TensorFlow, PyTorch, Scikit-learn AI/GenAI: prompt engineering (preferred), Claude CLI/Code(preferred), LLMs(preferred) Hugging Face, OpenAI APIs Data Tools (Optional): Pandas, NumPy, Spark APIs & Microservices development Version control (Git) Cloud & DevOps: Experience with AWS, Containers: Docker, ECS/EKS, CI/CD pipelines (GitHub Actions ...

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 ...

engineering best practices Identify opportunities for process improvement and platform optimisation Work with modern AI-assisted development tooling where appropriate Technical Environment Python Pandas/NumPy/Polars/PySpark Async processing/coroutines AWS cloud technologies Databricks Docker Relational and non-relational databases CI/CD and automated testing ...

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 ...

support vital national security projects. In order to be successful, you will have the following experience: Experienced in the Python data stack (PySpark, numpy, pandas, scikit-learn, etc.) Experienced within AWS-based infrastructure and services Excellent communication skills, able to work with customers to shape requirements Hold active SC clearance ...

support vital national security projects. In order to be successful, you will have the following experience: Experienced in the Python data stack (PySpark, numpy, pandas, scikit-learn, etc.) Experienced within AWS-based infrastructure and services Excellent communication skills, able to work with customers to shape requirements Hold active SC clearance ...

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 ...

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. ...

building production-quality software, internal applications, or data products beyond notebooks and dashboards Strong experience with scientific computing and machine learning libraries such as pandas, NumPy, SciPy, scikit-learn, statsmodels, PyTorch, TensorFlow, XGBoost, or equivalent tools Experience building and deploying software services, APIs, data pipelines, or internal platforms using tools ...

Python and R is crucial for data manipulation, analysis, and implementing algorithms. Python is favored for its simplicity and extensive libraries (like NumPy and pandas), while R is preferred for statistical analysis and data visualization. Statistical Analysis: A strong foundation in statistics and probability is necessary for analyzing data accurately ...

Python and R is crucial for data manipulation, analysis, and implementing algorithms. Python is favored for its simplicity and extensive libraries (like NumPy and pandas), while R is preferred for statistical analysis and data visualization. Statistical Analysis: A strong foundation in statistics and probability is necessary for analyzing data accurately ...

/CD pipelines. Experience with Redis, Celery, RabbitMQ, or Kafka. Familiarity with microservices architecture. Knowledge of AI/ML libraries such as Pandas, NumPy, TensorFlow, or PyTorch is a plus. Qualificat ...

internal data science capabilities. Skills & Experience Significant commercial experience in Data Science, Machine Learning, or Advanced Analytics. Strong Python skills with experience using pandas, NumPy, Jupyter, and related tools. Hands-on experience building and deploying predictive models in production environments. Experience with pricing, forecasting, revenue optimisation, risk modelling, or similar ...

Skills and Experience Strong commercial experience developing machine learning solutions in Python Solid understanding of the Python ML ecosystem including libraries such as NumPy, pandas, and scikit learn, with exposure to PyTorch or TensorFlow Experience building and deploying containerised services and APIs Working knowledge of SQL and data driven application ...

good working knowledge of SQL and relational databases. Data Analysis Tools: Experience working with structured datasets and executing data transformations using libraries like Pandas and NumPy. Version Control: Practical experience using Git. Beneficial Requirements Experience with cloud platforms (Azure is preferred, or AWS/GCP). An understanding of Docker ...

stability and performance over time. Required Skills and Qualifications Technical Expertise (The Core) Programming: Expert proficiency in Python and its core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation ...

structured, semi-structured, or unstructured data, especially large-scale text or content datasets. Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib. The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical ...

Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. Proficiency in Python for data science (pandas, NumPy, scikit-learn, statsmodels) and SQL for data extraction and analysis. Hands-on experience with Looker - LookML modeling, dashboard development, and content management. Experience training ...

Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field. Proficiency in Python for data science (pandas, NumPy, scikit-learn, statsmodels) and SQL for data extraction and analysis. Hands-on experience with Looker - LookML modeling, dashboard development, and content management. Experience training ...

support cross- community meetings and working groups Assimilate large volumes of information, and independently produce reports using data science focused libraries such as Pandas, Scikit, TensorFlow and Gensim Clearance: Must possess and maintain a TS/SCI clearance Bonus points for Masters in Data Science, Data Analytics, Informatics, Statistics ...

Python or R, SQL, No SQL. Assist in developing predictive and statistical models Write and optimize queries using SQL. Familiarity with data manipulation libraries (Pandas, NumPy), Understanding of statistics and probability. Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch. Preferred Skills: Hands on experience in coding ...

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 ...

5+ years of experience developing AI/ML applications and data-driven solutions • Excellent knowledge of Python and core data science libraries such as pandas, scikit-learn, LangChain, etc. • Experience with LLMs, including foundation model APIs, prompt engineering, and retrieval augmented generation • Substantial depth and breadth across state ...

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 ...