126 to 150 of 281 Permanent Pandas Jobs

Notebooks, Geoprocessing Tools). Desired Skills: Experience developing geospatial products using manually collected data (e.g., photos, GPS, drones). Experience with data science tools and formats such as SciKit, Pandas, GeoPandas, JSON, and GeoJSON. Knowledge of advanced GIS tools and technologies (e.g., Esri Portal, Tile Servers). Education & Certifications: Bachelor's degree or professional certification in GIS, Geography, Computer Science More ❯

lending strategy (SME or consumer lending preferred). Strong quantitative background (degree in Maths, Engineering, Physics, or similar). Experience building and maintaining predictive credit models. Fluency in Python (Pandas, NumPy, SciPy, Matplotlib) and SQL. Experience with advanced modelling techniques (e.g., Monte Carlo, Bayesian modelling) is a plus. Strong communicator. Commercial mindset and strong instincts around risk and return. Experience More ❯

lending strategy (SME or consumer lending preferred). Strong quantitative background (degree in Maths, Engineering, Physics, or similar). Experience building and maintaining predictive credit models. Fluency in Python (Pandas, NumPy, SciPy, Matplotlib) and SQL. Experience with advanced modelling techniques (e.g., Monte Carlo, Bayesian modelling) is a plus. Strong communicator. Commercial mindset and strong instincts around risk and return. Experience More ❯

lending strategy (SME or consumer lending preferred). Strong quantitative background (degree in Maths, Engineering, Physics, or similar). Experience building and maintaining predictive credit models. Fluency in Python (Pandas, NumPy, SciPy, Matplotlib) and SQL. Experience with advanced modelling techniques (e.g., Monte Carlo, Bayesian modelling) is a plus. Strong communicator. Commercial mindset and strong instincts around risk and return. Experience More ❯

Science, Technology, Finance, Collections, Operations, and other stakeholders. What you'll need Excellent SQL skills. A drive to solve problems using data. Proficiency with the Python data science stack (pandas, NumPy, Jupyter notebooks, Plotly/matplotlib, etc.). Bonus skills include: Familiarity with Git. Experience with data visualization tools (Tableau, Looker, PowerBI, or equivalent). Knowledge of DBT. More ❯

data concepts effectively and confidently Build great relationships with Data Science, Technology, Finance, Collections, Ops and other stakeholders What you'll need Excellent SQL skills Python data science stack (pandas, NumPy, Jupyter notebooks, Plotly/matplotlib, etc) A drive to solve problems using data Experience in a management role What would be a bonus: Familiarity with Git Data visualization tool More ❯

and customers 3+ years of experience involving data analytics, machine learning models and AI principles and application in implementation and practical delivery. Experienced in Python development and tooling including Pandas, Scikit-learn or equivalent. A third level qualification in Computer Science, Software Engineering, Data Science or other related discipline. Experience with data exploration and visualisation. A theoretical and practical foundation More ❯

Linux development environment Preferred Qualifications: 2-5 years Python work experience Any GUI development experience (Qt/PyQt would be ideal) Experience with Python data science libraries such as Pandas, Numpy, and Scipy XMIDAS familiarity C/C++ Code Management (Git would be ideal) Familiarity with the Atlassian tools (JIRA, Stash, Confluence, and Jenkins) and Gitlab Ability to analyze and More ❯

explain and defend employed models, their interpretation and business value to the team and stakeholders Experience developing AI/ML algorithms and infrastructure Excellent knowledge of Python, NumPy and Pandas Experience with at least one of: XGBoost, LightGBM, CatBoost, Tensorflow, PyTorch, MOSEK, CVXPY Graduate-level research experience in Artificial Intelligence or related field, including work published and/or accepted More ❯

Science Preferred Qualifications: 9+ years of SW development (3-5 Python) Any GUI development experience (Qt/PyQt would be ideal) Experience with Python data science libraries such as Pandas, Numpy, and Scipy XMIDAS familiarity C/C++ Code Management (Git would be ideal) Familiarity with the Atlassian tools (JIRA, Stash, Confluence, and Jenkins) and Gitlab Ability to analyze and More ❯

in a fast-paced innovative environment Ability to work in a team with fast turnarounds, manage workloads effectively and readily assume additional responsibilities Exposure to data analysis libraries (e.g., pandas, numpy) and visualisation tools (Matplotlib, plotly) Understanding software testing principals and frameworks Preferred skills Knowledge of financial instruments and equity markets Familiarity with cloud services Familiarity with quantitative research methodologies More ❯

contribute to classified programs and technologies you are passionate about. Our small agile teams adapt to evolving customer and warfighter needs. Candidates must have extreme fluency in NumPy and pandas This is a 12 Month full time Contract or Contract to hire opportunity. Active Top Secret Clearance What You Will Do: MLOps, Model Engineering, Training on time series data. After More ❯

in computer science , Mathematics, Statistics, Business Administration or related field Advanced knowledge of SQL (joins, aggregations, CTEs and window functions) Good knowledge of Python, including popular Data Science packages (pandas, matplotlib, seaborn, numpy , sklearn ) Familiarity with what is happening under the hood of popular Machine Learning algorithms Strong problem-solving skills and attention to detail Strong communication and collaboration skills More ❯

s or PhD degree in a quantitative field. Proven experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with the ability to present complex data More ❯

for you if: Proficiency in Python for API and model development, including frameworks like Sklearn, Pytorch, and TensorFlow. Understanding of machine learning techniques. Experience with data manipulation libraries (e.g., Pandas, Spark, SQL). Experience with version control (Git). Cloud experience (Azure, GCP, AWS). Additional desirable skills include: Modeling experience in industry-relevant use cases. Familiarity with MLOps environments. More ❯

processes and tools: CI/CD, version control (git), testing frameworks, MLOps Comfortable working with Docker and containerised applications Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc. Experience using AWS or similar cloud computing platform Great communicator - convey complex ideas and solutions in clear, precise and accessible ways Team player who cares about accelerating More ❯

a similar role. Strong programming skills and a good understanding of software engineering principles and clean code practices. Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn More ❯

data science roles Creative problem-solving and solution scoping Strong grasp of mathematical, statistical concepts, and machine learning algorithms Proficiency in Python and data science libraries for example NumPy, Pandas, Scikit-learn, Keras SQL proficiency Experience with cloud environments for example Google Cloud Platform Version control management Ability to work efficiently without compromising quality Effective communication and data storytelling skills More ❯

a similar role. Strong programming skills and a good understanding of software engineering principles and clean code practices. Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn More ❯

work with Python and Django on an increasingly more service-oriented architecture. The rest of the tech stack include Django REST Framework, PostgreSQL, AWS, React.js, Kubernetes, Docker, Redis, Celery, Pandas, Numpy, Git, Jenkins. We have a very large but clean code base as we put significant emphasis on design patterns, code readability, automated testing, maintainability and extendability. Responsibilities Work with More ❯

tight deadlines whilst remaining organised Strong analytical approach to problems Technical skills: Proficiency in Python Proficiency with version control (Git) Familiarity with containerisation (Docker) Familiarity with data processing tools (Pandas, NumPy) Experience using machine learning frameworks like PyTorch or TensorFlow Familiarity with cloud platforms and their ML services Benefits: MOST IMPORTANT: Your career Mentorship from senior machine learning engineers Access More ❯

coursework, internships, or self-initiated projects You've got practical Python skills - maybe from significant coursework, personal projects, or internships - and you're comfortable exploring data using libraries like pandas or numpy You've had hands-on experience with structured or semi-structured data, including tasks like designing schemas, cleaning messy datasets, or validating results - perhaps through coursework, Kaggle competitions More ❯

Experience delivering data science or data engineering solutions into production. You're comfortable writing production-grade code, not just notebooks. Strong Python and SQL skills, including the basic libraries (Pandas, Numpy, ScikitLearn). You value writing clean, maintainable, and tested code. Proven ability to design, build, and maintain data pipelines and tools from scratch that are reliable, maintainable, and scalable. More ❯

science in finance, insurance or Ecommerce is an advantage but not required Experience of deployment in a cloud environment Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas Experience with API development SQL experience Software engineering experience DevOps/MLOps experience Good working understanding of CI/CD If you hold the experience and technical skills outlined above More ❯

tight deadlines whilst remaining organised Strong analytical approach to problems Technical skills: Excellence with Python Excellence with version control (Git) Proficiency with containerisation (Docker) Proficiency with data processing tools (Pandas, NumPy) Experience using machine learning frameworks like PyTorch or TensorFlow Familiarity with cloud platforms and their ML services Benefits: MOST IMPORTANT: Your career Mentorship from senior machine learning engineers and More ❯