1 to 25 of 149 Pandas Jobs

Profile Essential Skills/Knowledge/Experience Data Science & ML Supervised and unsupervised learning Time series, NLP, recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps & Deployment Model lifecycle management CI/CD pipelines ...

patterns Your ProfileEssential Skills/Knowledge/ExperienceData Science & ML Supervised and unsupervised learning Time series, NLP, recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps & Deployment Model lifecycle management CI/CD pipelines ...

Platform (GCP). Bonus points for experience with AI, Machine Learning (PyTorch/TensorFlow), LLM frameworks (MCP/Langchain), or scientific Python (NumPy/Pandas)—though this is absolutely not necessary to apply. Infrastructure as Code. Degree in CS/Maths/Physical Sciences/Engineering; advanced degrees welcome ...

stability and performance over time. Required Skills and Qualifications Technical Expertise (The Core) Programming: Expert proficiency in Python and its core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation ...

entity resolution. GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

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 ...

Science delivery with measurable impact Experience taking models into production and managing performance over time Prior experience leading or mentoring Data Scientists Strong Python (pandas, numpy, scikit-learn or similar) Strong SQL (complex joins, aggregations, analytical functions) Solid grounding in applied statistics, evaluation design, calibration, bias/fairness Experience working ...

Science delivery with measurable impact Experience taking models into production and managing performance over time Prior experience leading or mentoring Data Scientists Strong Python (pandas, numpy, scikit-learn or similar) Strong SQL (complex joins, aggregations, analytical functions) Solid grounding in applied statistics, evaluation design, calibration, bias/fairness Experience working ...

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 ...

others Both roles come with a bonus and strong long-term progression potential. 🧠 Key Technical Skills Advanced SQL (Postgres strongly preferred) Strong Python development (Pandas essential) Experience with commodities pricing/financial markets Building and maintaining data pipelines (ETL/ELT, streaming) Working with time-series/analytical databases (e.g. ...

Deep understanding of object-oriented design, concurrency, and high-performance distributed systems Proficient in Python; Including use of libraries such as NumPy, SciPy and Pandas for quantitative analysis and prototyping Proven experience applying numerical optimisation techniques and/or machine learning methods to pricing, trading or market-related problems Prior ...

optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing ...

Required · Graduation in Information Technology/Computer Science · Minimum 8 years of experience · Strong proficiency in Python for data science, including libraries such as Pandas, NumPy, Scikit‐learn, PyTorch, or TensorFlow. · Experience building and deploying ML models into production systems. · Familiarity with LLMs, embeddings, vector databases, RAG patterns ...

continuous improvement. Technical Experience Were looking for experience in many of the following areas: Strong Python skills and familiarity with ML libraries such as Pandas, NumPy, and scikit-learn. Experience with frameworks such as TensorFlow, Keras, or PyTorch. Exposure to gradient boosting tools such as XGBoost, LightGBM, or CatBoost. Experience ...

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 ...

results. Experienced in engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow ...

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 ...

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 ...

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 ...

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 ...

leading university is a great indicator, though it's your depth of applied expertise that matters most. Technically, you bring: Python fluency (NumPy, Pandas, Scikit-Learn, PyTorch) and solid TypeScript/API skills Hands-on experience with LLMs prompt engineering, evaluation, RAG architectures, safety considerations Cloud-native development ...

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 ...

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 ...