16 to 40 of 392 Pandas Jobs

integer programming, heuristics) Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit‐learn, pandas, numpy, gurobi, etc.) to solve real‐life problems and visualise the outcomes (e.g., seaborn) Proficient in working with cloud platforms (AWS preferred), code versioning ...

Proven ability to translate business problems into measurable analytical outcomes. Experience taking models from development into production environments. Python and associated data science ecosystem (Pandas, NumPy, Scikit‐learn). Machine learning techniques including classification, regression, clustering and anomaly detection. Experience with Generative AI, LLMs, RAG architectures or agent‐based ...

Computer Science, Mathematics, Statistics or another STEM-related discipline. Desirable Skills Experience with cloud platforms such as AWS, Azure or GCP . Experience with Pandas, NumPy and Scikit-learn . Knowledge of data visualisation tools such as Power BI or Tableau. Experience with Git/version control. Exposure to Generative ...

computer vision, machine learning, or statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge ...

Linux environment Nice to have: Advanced data engineering experience in Python, e.g. with libraries like Dagster, Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models ...

scientists, and product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience with React (hooks, state management, component architecture) Experience building data pipelines and working with structured and unstructured data Solid understanding ...

Excellent communication skills with the ability to communicate concepts clearly and precisely Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES Experience as a Data Architect or Senior Manager Proven track record ...

Working You’ll work in a modern data and machine learning environment. The role is likely to involve: Python, including libraries such as Pandas, NumPy and scikit‐learn. SQL and large structured datasets. Cloud data platforms such as Snowflake, Databricks or similar. Git‐based version control and code review. ...

analytical outcomes. Desirable Well developed experience in a Lloyd’s syndicate, managing agent, London Market broker or specialty (re)insurer. Python for data analysis (pandas/notebooks) and an appreciation of wider data science techniques, enough to collaborate credibly with Data Scientists and Actuarial. Hands‐on experience applying AI/ ...

acquisition, file parsing and format handling, data validation, and the development of packaged, scheduled jobs. Familiarity with common data libraries such as requests and pandas is expected. Demonstrated experience acquiring and integrating data from heterogeneous sources, including delimited, fixed-width, JSON, and XML file formats; REST APIs requiring authentication, pagination ...

from concept through to production. Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative ...

skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

production‐grade backend systems at scale. Core Technical Skills Strong proficiency in Python as a primary backend language. Hands‐on experience with FastAPI and Pandas for building data‐driven API services. Solid experience with PostgreSQL – schema design, query optimization, and migrations. Experience with RabbitMQ or similar message brokers for asynchronous ...

value What We’re Looking For Essential experience Significant experience building, training and deploying machine learning models Strong Python skills with experience using NumPy, Pandas, SciPy and modern ML frameworks such as PyTorch or TensorFlow Experience working with large-scale unstructured data Experience building and deploying production-ready NLP systems ...

processing methods (streaming vs batch)Familiarity with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.), cloud platforms (AWS, Azure, GCP) and engineering tools (Pandas, Spark, dbt, LangChain, etc.)Exposure to modern software development practices, including version control (Git) and foundational concepts in DevOps and MLOps/LLMOps ...

version control. Good understanding of algorithms, data structures, and software design principles. Familiarity with data manipulation and analysis tools such as Pandas, NumPy, and SQL. Experience with, or a strong willingness to develop skills in, the Power Platform, including Power Apps, Power Automate, Power Pages and Dataverse. Basic understanding ...

strong foundation in system design, data storage, and reliability with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.) and data engineering tools (e.g., Pandas, Spark, dbt, etc.). Hands-on experience with MLOps/LLMOps principles, including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse ...

scalable SaaS platform. Any other ad hoc duties that may be required from time to time Technical Requirements: Proven experience with Python, especially Pandas and NumPy Mastery of SQL and PostgreSQL: schema design, complex queries, indexing and performance optimisation, beyond basic querying Experience with pipeline orchestration and scheduling Proven ability ...

analytical approach. Ability to work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review ...

analytical approach. Ability to work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review ...

analytical approach. Ability to work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review ...

analytical approach. Ability to work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit‐learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review ...

Strong understanding of core ML concepts - supervised/unsupervised learning, model evaluation, feature engineering - and broad familiarity with common algorithms and architectures. Strong Python (pandas, NumPy, etc.) and SQL skills Comfortable with the standard ML toolkit: Git, Docker, scikit-learn, PyTorch or TensorFlow, and ML pipelines. Hands-on experience with ...

including Power Pivot, Power Query, DAX, data models and complex financial modelling. Working knowledge of Python for data manipulation and automation, for example using pandas and scripting against vendor APIs. Experience building or maintaining ETL and data pipelines and working with structured data at scale. Understanding of IT infrastructure ...

between technical developers and business teams, showcasing strong leadership, creativity, and ethical problem-solving. Technical Expertise & Tools Python: Advanced, production-grade proficiency (Pandas, NumPy, FastAPI/Flask) with an absolute focus on writing clean, modular, and highly testable code. SQL: Expert querying, database design, partitioning, and optimization strategies for large ...