1 to 25 of 277 Pandas Jobs

agents).Strong proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit-learn, pandas, NumPy).Proven experience integrating AI services with enterprise systems via APIs and event-driven architectures.Practical experience with LLMs, prompt engineering, RAG and tools/plugins ...

technical audiences, advocating for interpretability and audit best practices.Experience working with structured and unstructured datasets.Proficient in Python, leveraging key data science libraries (NumPy, Pandas, scikit-learn) and applying object-oriented programming principles to develop efficient, scalable solutionsHands-on experience experimenting with Generative AI (e.g. LangChain, Hugging Face, LlamaIndex).Experience working ...

influence stakeholders as well as present complex findings clearly to both technical and non-technical audiencesStrong coding skills in Python (e.g. OOP, PySpark, Pandas, NumPy, etc) and experience with SQLStrong statistical & analytical skills (e.g. sampling methods), attention to detail, and a proactive empirical mindsetFamiliarity with data modelling & modern data tech ...

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 ...

engineering fundamentals: working with Parquet, Hive-partitioned datasets, and SQL against large tables (Athena/Presto). Solid working knowledge of the PyData stack — pandas and NumPy for data manipulation, Jupyter for experimentation, matplotlib/Seaborn for visualisation — and experience troubleshooting data-quality issues.Testing discipline with PyTest and a commitment ...

Docker and Kubernetes for scalable production systemsFamiliarity with distributed computing frameworks (e.g., Spark, Dask), cloud platforms (e.g., AWS, Azure, GCP), and analytics libraries (e.g., pandas, numpy, matplotlib)Exposure to DevOps, DataOps, and MLOps concepts and best practicesExperience with core technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/ ...

pipelines in a professional setting (e.g., internship) is a plusAbility to write clean, maintainable, scalable, and robust code in PythonFamiliarity with analytics libraries (e.g., pandas, numpy, matplotlib), distributed computing frameworks (e.g., Spark, Dask), and cloud platforms (e.g., AWS, Azure, GCP)Basic understanding or exposure to containerization technologies such as Docker ...

grounding. Technical Proficiency Machine learning algorithms: linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks Data science tools: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras Cloud computing platforms: AWS, Azure, GCP Natural language processing: transformer models, attention mechanisms, word embeddings Computer vision: convolutional neural networks, recurrent neural ...

communication skills, with the ability to explain complex technical AI concepts to non-technical business leaders. Advanced proficiency in Python and relevant libraries (NumPy, Pandas, PyTorch, or TensorFlow). Experience with Cloud AI Services (Azure AI Studio, AWS Bedrock, or Google Vertex AI [Preferred]). Knowledge of SQL and advanced ...

Stan/PyMC), or ensemble methods. Familiarity with rigorous experimentation: online/offline evaluation, data leakage prevention, and model governance. Tech Stack Python, SQL, pandas/numpy/scipy, PyTorch/sklearn Airflow/dbt, Kafka (or equivalents), Postgres/BigQuery Docker, Kubernetes (optional), CI/CD (GitHub Actions) Observability ...

Azure) and modern MLOps tooling (e.g. MLflow, Weights & Biases, DVC, Airflow) Strong experience with Python and associated scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit-learn, etc. Strong software engineering practices including version control, code review, software testing methodologies, and continuous integration; experience with ...

data experience, and a passion for building scalable, high-quality ML and data solutions in production environments. Essential Experience Strong programming skills in Python (Pandas, NumPy, etc.). Proficiency in SQL for data querying and transformation. Hands-on experience with Machine Learning techniques and frameworks (e.g., scikit-learn, TensorFlow, PyTorch ...

team standards for data extraction, complex aggregation, and resilient exception management, contributing to their ongoing improvement. Statistical Analysis & Quality Apply advanced, critical quantitative methods (Pandas, NumPy) to process raw data and derive actionable insights. Implement automated frameworks to ensure enterprise-grade data quality and continuous validation. Strategic Reporting Go beyond ...

Python experience and knowledge, with the ability to write stable, scalable and maintainable code. Experience with data science Python libraries such as Sckit-learn, Pandas, NumPy, PyTorch, PySpark, LightGBM. Have worked with a cloud service, such as AWS. Familiarity developing Infrastructure as code (e.g Terraform, cloudformation). Have some experience ...

skills Experience of cloud platforms (AWS, Azure, or GCP) Experience of containerisation (Docker) and orchestration (Kubernetes) Exposure to data engineering tools/libraries (e.g. Pandas, NumPy) or NLP libraries Knowledge of message queues/event-driven architecture (e.g. RabbitMQ, Kafka) Understanding of CI/CD tools (e.g. Jenkins, GitHub Actions ...

machine learning techniques, focused on timeseries data and text Strong programming skills in Python and experience with standard data science libraries such as pandas, numpy, scikit-learn, tensorflow, pytorch Experience working with data systems, structured and unstructured databases such as ClickHouse or MongoDB Familiarity with APIs, pipelines, kubernetes and linux ...

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 ...

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 ...

translate business problems into measurable analytical outcomes.* Experience taking models from development into production environments.### Technical Skills* 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 AI solutions. ...

data, dashboards and AI-enabled insight confidently and responsibly. What we're looking for Extensive experience using python, especially using libraries such as Pandas, scikit-learn and NumPy. Strong programming skills in SQL or Spark SQL Experience in Natural language processing and working and developing LLMs Full ML model lifecycle ...

implementing data science processes. Experience in translating customer requirements into technical requirements and development objectives. Python expertise covering standard data science libraries (NumPy, pandas, matplotlib, Scikit-learn, PyTorch, etc...), web frameworks (Flask or FastAPI) and visualisation (Dash, Plotly, & Streamlit). Proficient in SQL. Working with unstructured data Building customer ...

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 ...

secure use of data and AIRequired Skills:Experience in data science, machine learning, or applied analyticsStrong proficiency in Python and common ML libraries (pandas, NumPy, scikit‐learn, TensorFlow, PyTorch)Experience designing, training, and evaluating machine‐learning modelsSolid understanding of statistical methods, predictive modelling, and experimental designExperience working with large ...

/stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required.Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.).Proven experience developing, refining, and monitoring NLP models.Familiarity with database management tools and techniques (e.g., SQL, Selenium, S3, Sagemaker ...

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 ...