16 to 40 of 102 Pandas Jobs

deliver insights and ensure seamless data availability for decision‐making. Your Skills Strong expertise in Python and Scala, with hands‐on experience in Pandas, NumPy, Scikit‐learn, PySpark, and MLlib. Solid SQL skills and experience working with large‐scale, big‐data frameworks (e.g., Spark, Hadoop). Familiarity with major cloud ...

Experience setting up CI/CD pipelines Understanding of service deployment, monitoring, and troubleshooting Data Science/Analytics Experience with data analysis using Python (pandas, numpy) Understanding of data pipelines and ETL processes AI/LLM Engineering Experience integrating LLM APIs (OpenAI, Anthropic, Gemini, or open-source equivalents) into production ...

welcome applications from women who are passionate about machine learning and eager to grow: Strong Python skills and experience with ML libraries (pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, Keras, PyTorch). Familiarity with model deployment and serving tools (ONNX, TensorRT, TensorFlow Serving, TorchServe). Experience with ML lifecycle ...

live production environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). ...

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 ...

documentation, and team knowledge sharing. Ideal Background Strong analytical mindset and passion for deriving actionable insights from complex data. Proficient in Python or R (pandas, NumPy, scikit-learn, TensorFlow or equivalent) and SQL. Experience as a data scientist on client-facing software solutions, ideally in optimisation or energy-focused domains. ...

enable capabilities such as intelligent document processing, conversational AI, and semantic search. Knowledge and experience of some of the following tools; Apache Spark, Databricks, Pandas for data processing and feature engineering SQL, MongoDB for structured and unstructured data management SageMaker, Azure ML for model deployment, tracking, and monitoring. Terraform, Ansible ...

postgraduate qualification a plus. Beyond that: Demonstrable experience shipping AI or ML systems to a live production environment Solid Python across the core stack: Pandas, NumPy, Scikit-learn, and PyTorch or TensorFlow Real hands-on experience with LLMs — fine-tuning, prompt engineering, agentic orchestration A working understanding of MLOps ...

distributed systems , CI/CD, testing frameworks, and deployment pipelines Experience designing or operating cloud‐native, production‐grade infrastructure Strong data manipulation skills ( Pandas, SQL ) Ability to optimise non‐deterministic systems through experimentation while balancing latency, cost, and quality Nice to Have Experience with AI‐assisted coding (Claude Code, GitHub ...

scaled full stack products Strong backend (Node.js, Python/Flask, FastAPI) and frontend (React, Next.js, Vue) fundamentals ML/data science proficiency: Python, SQL, pandas, scikit-learn, PyTorch/TensorFlow Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Proven ability to build data-secure, privacy-compliant infrastructure ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

feed ML models 2+ years of experience using Dask, RAPIDS, or in High Performance Computing 2+ years of experience with the PyData ecosystem (NumPy, Pandas, and Scikit-learn) Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM fine-tuning ...

Machine Learning (sci-kit learn, tensorflow, metaflow, MLOps) Preferred Experience: Experience with frameworks like Metaflow, Prefect, etc. Experience with geospatial libraries i.e. Raster, Geo-pandas, Vector databases Bright Purple is an equal opportunities employer: we are proud to work with clients who share our values of diversity and inclusion ...

seasoned Associate to Mid-level Software Engineer with hands-on Python experience. Familiarity with AWS Serverless and related technologies would be advantageous. Strengths in Pandas, Polars, Pytest, Postgres, and CI/CD is essential. If you're interested in Agile methodologies, and have a curiosity about DDD and Event-Driven ...

with your peers on technical direction within your team Required Skills and Experience Strong analytic skills related to working with unstructured datasets Python (PySpark, Pandas, PyArrow) Distributed data processing (Apache Spark) Data ETL (Apache Airflow, AWS Step Functions, Apache NiFi) Cloud services (AWS, Azure or GCP) Messaging/Streaming (Kafka ...

technical discussions, code reviews, and agile delivery Required Skills & Experience Essential 36+ years commercial experience in Applied ML or Data Science Strong Python (pandas, numpy, sklearn or similar) Strong SQL Experience building and iterating on predictive models Conditional (must meet at least 2 of the below) Time-series modelling 2+ ...

Qualifications Core Technical Skills Skill Area Requirements Programming Strong proficiency in Python for data manipulation and scripting. Familiarity with standard Python data libraries (e.g., Pandas, NumPy ). Database Expert-level proficiency in SQL (Structured Query Language). Experience writing complex joins, stored procedures, and performing performance tuning. Big Data Concepts ...