16 to 40 of 263 Pandas Jobs

IT and regulatory standards. Skills & Experience Strong proficiency in Python, with a focus on rapid prototyping and data driven applications. Solid understanding of multi-processing and AsyncIO. Experience with pandas, NumPy, and SQL for data analysis and transformation. Exposure to REST APIs, messaging systems, and integration with trading or risk platforms. Hands-on experience building front-end tools or GUIs. More ❯

IT and regulatory standards. Skills & Experience Strong proficiency in Python, with a focus on rapid prototyping and data driven applications. Solid understanding of multi-processing and AsyncIO. Experience with pandas, NumPy, and SQL for data analysis and transformation. Exposure to REST APIs, messaging systems, and integration with trading or risk platforms. Hands-on experience building front-end tools or GUIs. More ❯

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 ❯

Mentor junior engineers and contribute to engineering best practices Required Skills & Experience: 5+ years of experience building and maintaining data pipelines in production environments Strong Python and SQL skills (Pandas, PySpark, query optimisation) Cloud experience (AWS preferred) including S3, Redshift, Glue, Lambda Familiarity with data warehousing (Redshift, Snowflake, BigQuery) Experience with workflow orchestration tools (Airflow, Dagster, Prefect) Understanding of distributed More ❯

Mentor junior engineers and contribute to engineering best practices Required Skills & Experience: 5+ years of experience building and maintaining data pipelines in production environments Strong Python and SQL skills (Pandas, PySpark, query optimisation) Cloud experience (AWS preferred) including S3, Redshift, Glue, Lambda Familiarity with data warehousing (Redshift, Snowflake, BigQuery) Experience with workflow orchestration tools (Airflow, Dagster, Prefect) Understanding of distributed More ❯

design) Strong background in AI/ML with experience using frameworks such as TensorFlow, PyTorch, or Scikit-learn Proficiency in data handling and manipulation using libraries like NumPy and Pandas Experience with SQL databases for managing and accessing training data Knowledge of model deployment and scaling in enterprise or cloud environments (AWS, Azure, or GCP) Familiarity with containerization and orchestration More ❯

alignment between technology initiatives and business objectives. Required Qualifications: 6+ years of experience in full stack software development. Proficiency in sever side Python programming. Proficiency in data analysis using Pandas, Numpy, SciPy etc. Experience with object oriented design, distributed systems architecture, performance tuning. Experience with designing and programming relational database such as MySQL, RedShift, Oracle SQL Server, or Postgres. Experience More ❯

a thought leader in data science. Requirements 5+ years of experience in data science, machine learning, or AI model development. Expertise in Python, R, or Julia, with proficiency in pandas, NumPy, SciPy, scikit-learn, TensorFlow, or PyTorch. Experience with SQL, NoSQL, and big data technologies (Spark, Hadoop, Snowflake, Databricks, etc.). Strong background in statistical modelling, probability theory, and mathematical More ❯

e.g., using type hints and understanding the limitations of the language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data More ❯

e.g., using type hints and understanding the limitations of the language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data More ❯

OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

deployment and performance tuning. Leveraging statistical methods, data analysis, and modern compute infrastructure to improve research and execution workflows. What you need Strong programming background, primarily in Python (NumPy, Pandas, SciPy, etc.). Solid understanding of computer science fundamentals – algorithms, data structures, and software design. Experience within a quant, trading, or financial markets environment (hedge fund, prop desk, or similar More ❯

deployment and performance tuning. Leveraging statistical methods, data analysis, and modern compute infrastructure to improve research and execution workflows. What you need Strong programming background, primarily in Python (NumPy, Pandas, SciPy, etc.). Solid understanding of computer science fundamentals – algorithms, data structures, and software design. Experience within a quant, trading, or financial markets environment (hedge fund, prop desk, or similar More ❯

Strong problem-solving skills and attention to detail. Eagerness to learn about trading systems, low-latency development, and financial markets. Experience with data analytics tools or frameworks (Python, SQL, Pandas, etc.) is advantageous but not essential. A degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Why Join Us Work in a dynamic, high-impact More ❯

Strong problem-solving skills and attention to detail. Eagerness to learn about trading systems, low-latency development, and financial markets. Experience with data analytics tools or frameworks (Python, SQL, Pandas, etc.) is advantageous but not essential. A degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Why Join Us Work in a dynamic, high-impact More ❯

Manage cloud-based and on-prem setup Requirements: 25 years experience in ML engineering/MLOps roles Strong proficiency in Python and experience with relevant ML libraries/frameworks (pandas, numpy, sklearn, TensorFlow, PyTorch) Strong understanding and experience in implementing end-to-end ML pipelines (data, training, validation, serving) Experience with ML workflow orchestration tools (e.g., Airflow, Prefect, Kubeflow) and More ❯

scalability of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow More ❯

scalability of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow More ❯

related field. Deep understanding of option pricing theory (Black-Scholes, local/stochastic volatility, Monte Carlo). Expert Python developer with strong numerical and vectorized coding skills (NumPy, SciPy, Pandas). Experience building and calibrating volatility surfaces and handling risk measures (Greeks, VaR, sensitivities). Strong background in stochastic calculus, numerical methods, and optimization. More ❯

related field. Deep understanding of option pricing theory (Black-Scholes, local/stochastic volatility, Monte Carlo). Expert Python developer with strong numerical and vectorized coding skills (NumPy, SciPy, Pandas). Experience building and calibrating volatility surfaces and handling risk measures (Greeks, VaR, sensitivities). Strong background in stochastic calculus, numerical methods, and optimization. More ❯

e.g., Mathematics, Statistics, Computer Science, Engineering, Physics, Economics); advanced degree preferred. Strong expertise in statistical modelling, Bayesian inference, and machine learning. Proficient in Python (using libraries such as NumPy, pandas, scikit-learn, PyMC or Stan) Experienced in SQL. Ability to write efficient and robust queries. Demonstrated experience working with large and complex datasets. Ability to communicate complex analytical concepts clearly More ❯

e.g., Mathematics, Statistics, Computer Science, Engineering, Physics, Economics); advanced degree preferred. Strong expertise in statistical modelling, Bayesian inference, and machine learning. Proficient in Python (using libraries such as NumPy, pandas, scikit-learn, PyMC or Stan) Experienced in SQL. Ability to write efficient and robust queries. Demonstrated experience working with large and complex datasets. Ability to communicate complex analytical concepts clearly More ❯

validation techniques such as cross-validation, bootstrapping, and assessing the statistical significance of model improvements. Excellent knowledge of data analysis, visualization, and preprocessing techniques. Familiarity with tools such as Pandas, NumPy, and Matplotlib. Experience deploying Classical and Modern Time Series Forecasting solutions using tools such as Neural Prophet, SARIMA, Chronos, etc Familiar with cloud-based machine learning platforms such as More ❯

GitHub Actions, CircleCI - depending on team) Monitoring/Logging (CloudWatch, Prometheus, Grafana - nice-to-have) Data/Scientific Computing/ML Tools Python libraries for data processing, visualization, ML (Pandas, NumPy, Matplotlib, scikit-learn, PyTorch, TensorFlow) Robotics frameworks or internal research computing tools (if applicable) Strong Communication Skills - able to clearly articulate technical concepts to peers, leadership, and cross-functional More ❯