26 to 50 of 100 Remote/Hybrid Pandas Jobs

training of AI/ML solutionsSkills required: Overall 8+ years of experience. 5+ Years of strong Python coding skills and python libraries (like NumPy, Pandas etc.) 3 Years of solid understanding of generative AI models (GANs, VAEs, LLMs) and their underlying principles Strong experience in using Neo4J, Mongo DB Experience ...

degree in a technical subject. Physical sciences or mathematics are preferred. Strong Python skills and competency across the Python data science ecosystem such as pandas, numpy and scikit-learn, or a highly transferable equivalent. Experience working with LLMs and agentic AI systems, including harnesses, RAG, context engineering and evaluations. Experience ...

What we’re looking for: Proficiency in Python (and at least one other language a plus). Experience with key libraries such as PyTorch, Pandas, Hugging Face Transformers, or similar AI toolkits. Working knowledge of common models, and their use cases and experience applying them to solve specific problems. Solid ...

What we're looking for: Proficiency in Python (and at least one other language a plus). Experience with key libraries such as PyTorch, Pandas, Hugging Face Transformers, or similar AI toolkits. Working knowledge of common models, and their use cases and experience applying them to solve specific problems. Solid ...

deliver on project objectives. Masters degree in a STEM field (maths, science, engineering etc.) or equivalent Strong programming skills in Python (e.g., NumPy, Pandas, scikit-learn, TensorFlow/PyTorch). Demonstrable experience in creating and developing Python libraries. Demonstrable experience designing, implementing and training machine learning models from scratch. Strong ...

Skills and Experience Strong commercial experience developing machine learning solutions in Python Solid understanding of the Python ML ecosystem including libraries such as NumPy, pandas, and scikit learn, with exposure to PyTorch or TensorFlow Experience building and deploying containerised services and APIs Working knowledge of SQL and data driven application ...

Experience in managing data and implementing data science processes. Experience in translating customer requirements intotechnical requirements and development objectives. Pythonexpertisecovering standard data sciencelibraries (NumPy, pandas, matplotlib, Scikit-learn,PyTorch, etc),web frameworks (Flask or FastAPI) and visualisation(Dash,Plotly,&Streamlit). Proficient inSQL. Working with unstructured data Building customer ...

Experience in managing data and implementing data science processes. Experience in translating customer requirements intotechnical requirements and development objectives. Pythonexpertisecovering standard data sciencelibraries (NumPy, pandas, matplotlib, Scikit-learn,PyTorch, etc),web frameworks (Flask or FastAPI) and visualisation(Dash,Plotly,&Streamlit). Proficient inSQL. Working with unstructured data Building customer ...

without: Applied data science expertise Machine learning and AI delivery Generative AI/LLM experience Strong Python skills and familiarity with core libraries (pandas, NumPy, scikit‐learn) Deep learning and NLP stacks (PyTorch, HuggingFace Transformers) MLOps and model operationalisation Additional Requirements: Security clearance (SC/BPSS) Familiarity with regulated industries ...

least 2 years’ experience working as a data engineer (ideally consulting/financial services) – salary and level will reflect experience. Proficiency in Python (pandas, numpy) Professional experience with Azure cloud services (AWS/GCP acceptable with deeper experience) Strong experience deploying clean, maintainable, production-level code. Basic understanding ...

Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) < Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management ...

Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management ...

Statistics or Maths.* Strong Python coding experience/knowledge essential. Knowledge of git and CI/CD practices. Demonstrable proficiency with packages such as Pandas, Sklearn; Pytorch or Keras.* Knowledge of SQL and Excel; experience with Databricks would be welcome.**Person specification*** Excellent analytical skills and attention to detail.* Works ...

verbal and written communication Share ideas with the wider team, learn from and contribute to the body of knowledge Key Skills Experience using Python (pandas, numpy, scikit-learn) and SQL Theoretical understanding of core ML techniques and statistical principles Strong numerical and analytical skills, comfortable working with large datasets Confident ...

ability to design end-to-end models, write production-quality code, and make independent modelling and architecture decisions. Advanced Python and SQL, including pandas, scikit-learn, and XGBoost/LightGBM. Experience in at least two of the following: forecasting, segmentation, recommender systems, ranking, or behavioural modelling. Proven delivery ...

deploy Machine Learning capabilities and techniques into other systems. Familiarity with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit‐learn Take pride in writing clean, reusable, maintainable and well‐tested code A desire to learn and embrace new and emerging ...

with data from multiple sources and formats. Working with cloud-based data platforms, ideally Microsoft Azure. Python: core data science libraries such as numPy, pandas/polar If you meet all of the criteria as set out above, please send me a targeted ...

Python for automation, parsing, rules engines, and data quality checks, ability to write maintainable code. Experience using Python packages for data wrangling (e.g. Pandas, Polars), modelling (e.g. scikit-learn) and visualization (e.g. matplotlib) Experience with modern data tooling (for example, Spark, Azure Data Factory) or ability to implement equivalents with ...

structures and algorithms for efficient data processing and model optimization Error handling and debugging using try-catch blocks, logging, and debugging tools Data Processing: Pandas and NumPy for data manipulation, cleaning, and numerical operations SQLAlchemy or psycopg2 for database connectivity and ORM operations Boto3 for AWS service integration and automation ...

XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.). Strong knowledge of SQL and Python’s ecosystem for data analysis (Jupyter, Pandas, Scikit‐Learn, Matplotlib). Strong software development skills (Python is the preferred language). Strong management and leadership skills – previous experience managing a team. Strong ...

skills and experience The successful candidate will have: Three or more years of commercial Data Science or applied analytics experience. Strong Python skills, including pandas, scikit-learn and common Data Science libraries. Advanced SQL skills and experience working with large or varied datasets. Commercial experience using Snowflake. A good grounding ...

metrics and explainability techniques Applying machine learning techniques within computer vision or natural language processing Using Python data science and visualisation libraries such as pandas, scikit-learn, statsmodels, matplotlib or seaborn, alongside deep learning frameworks such as TensorFlow or PyTorch Working with large datasets, data analysis, data warehouses, big data ...

data analysis and model prototyping to production deployment, integration, and ongoing monitoring. You are proficient in Python and its data/ML ecosystem (e.g. pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings. You have deployed models into live systems ...

building production systems that deliver measurable business impact Technical Mastery: High proficiency in Python and SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM) Systemic Problem Solving: Ability to work on unique ...

data analysis and model prototyping to production deployment, integration, and ongoing monitoring. You are proficient in Python and its data/ML ecosystem (e.g. pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings. You have deployed models into live systems ...