1 to 25 of 37 Remote Pandas Jobs

quantitative modelling bridging the gap between data and lived football judgement Essential Requirements Technical Skills Advanced proficiency in Python and the data science stack (pandas/polars, scikit-learn, NumPy, matplotlib/plotly) Strong SQL skills ability to design schemas, write complex queries, and manage relational data across large datasets ...

Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker ...

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 ...

such as Tableau or Power BI. Published work, patents or conference presentations related to AI or data science in finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree‐based models, neural networks, MLOps ...

MLOps: Establish CI/CD pipelines and manage model deployment using Kubernetes/OpenShift and MLOps principles. Technical Requirements Core Programming: Expert-level Python (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow, FastAPI, LangChain, LlamaIndex). Generative AI: Deep experience with LLMs (Gemini, OpenAI, Claude, Llama) and evaluating model safety/ ...

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. ...

time‐series databases, visualization tools). Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree‐based models, neural networks; MLOps, model deployment, automated testing. Data ...

clearly Required Qualifications Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, Mathematics , or related field Strong foundation in Python (Pandas, NumPy, Scikit-learn) Understanding of machine learning concepts (regression, classification, clustering) Experience with data visualization tools (Matplotlib, Seaborn, or similar) Familiarity with SQL and working ...

from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience ...

scikit-image, PIL) and classical CV algorithms (edge detection, thresholding, color spaces). Data Analytics Fluency: Experience working with standard data manipulation libraries (NumPy, pandas, scikit-learn, SciPy). Communication: Advanced English proficiency to collaborate effectively in a global environment. Bonus Points (Nice to Have) Hands-on experience with Vision ...

deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring ...

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 ...

professional experience. You must have "under-the-hood" knowledge of Python, specifically for building high-throughput microservices and complex data pipelines using FastAPI, Pandas, and NumPy . The RAG & Agentic Expert: This is the "Critical" requirement. Our client needs someone with deep hands-on experience building Retrieval-Augmented Generation ...

professional experience. You must have 'under-the-hood' knowledge of Python, specifically for building high-throughput microservices and complex data pipelines using FastAPI, Pandas, and NumPy . The RAG & Agentic Expert: This is the 'Critical' requirement. Our client needs someone with deep hands-on experience building Retrieval-Augmented Generation ...

operate independently and take ownership of complex problems Strong communication skills, with the ability to explain technical concepts clearly Technical Environment Python (e.g. pandas, scikit-learn, TensorFlow/PyTorch where relevant) SQL and large-scale data processing Cloud-based environments (e.g. AWS, Azure, or similar) Experience with model deployment, monitoring ...

Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning ...

internships/placements welcome in addition) Strong SQL skills and confidence working with relational data and large datasets Strong Python for analysis/automation (pandas, NumPy; good coding hygiene) Essential: Dashboarding experience in Power BI, Tableau, or Looker (building and maintaining stakeholder-facing dashboards) Solid understanding of analytics fundamentals: data ...

collaborate with engineering teams to improve data pipelines and outputs. Requirements: 5+ years experience in data science, analytics, or related fields; strong Python skills (pandas, numpy); solid grounding in statistics and data analysis; experience working with structured and semi-structured data; ability to translate complex data into clear insights. Nice ...

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). ...

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). ...

Postgres, REST APIs, SFTP, Websockets OOP + Asynchronous Design Patterns PowerQuery/DAX/M Industry standard libraries used in software development within finance (pandas, numpy, scipy etc) MS Graph * Experience with the following technologies is nice to have: NodeJS Grafana VBA OpenAI API Cross OS file shares Profile ...

infrastructure and tooling stack What They’re Looking For 4+ years experience in machine learning, data science, or AI engineering Strong Python skills (NumPy, Pandas, PyTorch/TensorFlow) Experience working with biological or biomedical data (industry or academia) Solid understanding of ML fundamentals (supervised/unsupervised learning, model evaluation, etc. ...

within a product or operational environment, with demonstrable impact on decision-making Advanced hands-on experience with data processing and analysis tools (SQL, Python, Pandas, etc), with a bias towards exploration, insight and explanation Proven ability to understand legacy datasets/pipelines and to evaluate their fitness ...

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 ...

Senior Data Scientist you will have: At least 4 years experience in Statistics and Machine Learning Experience with Python Machine Learning libraries (NumPy, Pandas, SKLearn etc) At least 3 years Python programming experience Experience applying models to Big Data Familiar with the principles of Continuous Integration and Deployment (CI/ ...