1 to 25 of 30 Remote/Hybrid scikit-learn Jobs in England

setting. Education: Relevant Software Engineering/Computer Science degree. Technical Skills Programming Languages: Python, Java, C++, C#, TypeScript, JavaScript Machine Learning: TensorFlow, PyTorch, Scikit-learn GenAI/LLMs: OpenAI API, Hugging Face Transformers, LangChain, Langraph, RAG pipelines Data & Analytics: Pandas, NumPy, Spark, Databricks, Hadoop, Vector Databases, Snowflake Model ...

contribute to our internal library of proprietary tools and frameworks. Technical Profile Expert Programming: Mastery of Python and its ecosystem (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Experience writing production-ready, modular, and well-tested code. Advanced Modeling: Deep theoretical and practical knowledge of Machine Learning. ...

patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear, mixed‐integer ...

patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear, mixed‐integer ...

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, k8s, FastAPI ...

Python Understanding of machine learning fundamentals (supervised/unsupervised learning, model evaluation, overfitting, etc.) Experience with common ML libraries such as PyTorch, TensorFlow, scikit-learn , or similar Solid foundation in data structures, algorithms, and software engineering principles Strong problem-solving skills and attention to detail Excellent communication skills ...

into production environments. Key skills and experience include: Strong programming skills in Python Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn Advanced knowledge of statistics, probability, and optimisation techniques Proven experience building, testing, tuning, and optimising machine learning models Comfortable working with large, complex ...

such as NLP, computer vision, audio, graphs, time-series or tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying ...

datasets, data preprocessing, feature engineering, and efficient data flow to ensure high-quality input for machine learning models. Optimizing models. Use tools like scikit-learn and Keras to fine-tune models for enhanced model performances Perform exploratory data analysis to identify patterns and insights. Develop and test statistical ...

years' experience as a data scientist in industry or related environments. Proficiency in Python and common ML/data libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Understanding of software and ML engineering best practices (git, package development, model deployment). Experience with cloud platforms, particularly ...

junior colleagues and share learnings across the team. Requirements: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow. Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments. Strong experiment design skills: hypothesis formulation ...

Skilled at working with non-technical stakeholders to scope, design and deliver effective ML solutions. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI ...

systems, personalisation, or deep learning is desirable but not essential. Solid Python skills and experience with ML libraries such as pandas, numpy, scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps practices ...

solutions Implement experiment tracking and monitoring Collaborate with data scientists and engineers What We're Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps ...

junior data scientists and help shape AI best practice Requirements Strong experience in AI, machine learning and statistics Python expertise (e.g. pandas, NumPy, scikit-learn, PyTorch, transformers) Experience deploying models and working with cloud platforms (AWS preferred) Ability to communicate complex technical concepts clearly Desirable AWS services (SageMaker ...

science practices tooling governance Essential Skills for the Data Scientist: Strong experience in data science using Python with libraries such as Pandas NumPy scikit-learn or similar Solid grounding in statistics probability machine learning techniques Proven experience working within cloud environments such as AWS Azure or GCP Experience ...

years' experience in ML/AI engineering or data science roles (senior level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record ...

with support from more experienced colleagues. Some experience presenting technical findings to non-technical stakeholders. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Any exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes ...

engineers to productionise models Communicate insights to technical and non-technical stakeholders Mentor junior team members Skillset: Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy) Experience with AWS cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision ...

stakeholders Mentor junior engineers and contribute to team best practices This role is for you if you have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live ...

experience delivering AI/ML projects end-to-end in production environments Strong Python skills with hands-on use of ML libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms ...

Fundamentals: You aren't limited to APIs. You have a background in training and evaluating models (TensorFlow/PyTorch/Keras/Scikit-learn) and know when a simple classifier is better than a generative model. Data Fluency: You understand how to build datasets from scratch (bootstrapping, crowdsourcing ...

Fundamentals: You aren't limited to APIs. You have a background in training and evaluating models (TensorFlow/PyTorch/Keras/Scikit-learn) and know when a simple classifier is better than a generative model. Data Fluency: You understand how to build datasets from scratch (bootstrapping, crowdsourcing ...

multiple domains (NLP, vision, audio, time series, tabular data). Proficient in Python and relevant ML/data science libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Experience with cloud-based model deployment (AWS) and ML engineering best practices. Excellent communication, problem-solving, and project delivery skills. ...

marketing, pricing, and promotional levers, and how they influence commercial performance. Solid Python skills for data manipulation, modelling, and visualisation (e.g., pandas, NumPy, scikit-learn). High proficiency with Microsoft Office, particularly Excel, PowerPoint, and Word. Exceptional attention to detail and a commitment to analytical rigour. Ability ...