1 to 25 of 297 Permanent Pandas Jobs

Engineering, AI, or related field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . More ❯

trading Requirements: Bachelor's degree or higher in CS, Engineering or other technical discipline Demonstrated ability to program in a scientific computing environment, preferably in Python/NumPy/Pandas and Java/C++ Experience working with distributed systems and large data sets Strong knowledge of algorithms, design patterns, OOP, threading, multiprocessing, etc. Experience with SQL, NoSQL, or tick databases More ❯

Plotly Dash applications in Google Cloud Platform (GCP).Experience working with Postgres Database and BigQuery.Experience with ETL/ELT tools and processes in Python/PySpark and SQL (e.g., pandas, numpy).Experience in Docker containerization and GCP development, debugging, and deployment.Experience in test-driven development using tools like unit test, pytest, mock.Familiarity with CI/CD development utilizing tools such More ❯

Financial Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

Financial Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

Financial Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

Financial Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

Financial Markets, especially in a Hedge Fund, Trading Firm, and/or working with Quant Trading Technology. Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

in place of a degree Experience with the following Data Science technologies Various machine learning libraries (i.e. Apache Spark, Scikit-learn, XGBoost, etc.) Data manipulation and pipeline libraries (i.e. Pandas, Polars, matplotlib, Plotly, numpy, scipy, etc.) Data science environments (e.g. Jupyter Notebook, Data Bricks, or Amazon Sage Maker) Experience implementing the data science process, developing experiments, reporting and explaining results More ❯

system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant More ❯

system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant More ❯

system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant More ❯

system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant More ❯

system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant More ❯

the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience building More ❯

the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience building More ❯

the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience building More ❯

the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience building More ❯

the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience building More ❯

accesses, and loading. Databases: PostgreSQL, NoSQL, Vector Databases, Graph Databases etc. ETL/ELT Concepts Data warehouse concepts SQL Competency in data exploration, analytics, and feature engineering. (Python Specific) Pandas/NumPy/Polars/PySpark Plotly/Matplotlib (some form of data visualization) Data encoding/normalizing/regularizing/etc. Understanding of Deep learning concepts and architectures like More ❯

that you work. The work space itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch More ❯

that you work. The work space itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch More ❯

processing and ML jobs, including the use of IAC to build data pipelines Expert knowledge of Python. An excellent knowledge of basic machine learning libraries, such as NumPy, SciPy, Pandas, Dask, PyTorch, Tensorflow, etc. A proven track record of linking data from multiple systems for scalable productionised solutions with security and monitoring best practices. Experienced with Cloud Security best practices. More ❯

ML libraries Experience with Docker, Kubernetes, and cloud AI platforms such as AWS Bedrock, Sagemaker, Azure ML, or GCP Vertex AI Working knowledge of data tools such as Spark, Pandas, SQL/NoSQL databases Security: TS clearance required Nice to Have Experience with LangChain, hybrid retrieval orchestration frameworks, or custom AI agent architectures Experience implementing custom authentication/authorization strategies More ❯

e.g., ingesting data, cleaning, etc.). Experience with Software/Data Science Concepts: Understanding of data structures, algorithms, and common data science techniques. Experience with data science tools like Pandas, NumPy, or similar libraries for data manipulation. Experience with Cloud/Distributed Systems: Familiarity with cloud platforms (AWS, Azure, etc.) is a plus, especially if the data pipeline is running More ❯