quantitative discipline eg. Statistics, Mathematics, Physics, Machine Learning Deep expertise in Python (production-level) and SQL Proficiency in machine learning libraries (eg. Pandas, scikit-learn, TensorFlow) and experience with MLOps frameworks for model deployment Exceptional communication skills, able to engage confidently with non-technical stakeholders Experience resolving operational more »
familiarity with elastic net logistic regression, random forest and XGBoost ensembles to work on supervised problems with structured, tabular data. We currently use Scikit-learn, and we're open to suggestions for additional libraries. Classification using K-means, K-Medoids or similar and the skills to evaluate solution more »
NLP , and LLMs Expert ability with ML/MLOps Experience mentoring/up-skilling more junior team members. Strengths in SQL , Python ( Pandas , Scikit - Learn , PyTorch ) PhD -level education and experience within Marketing is preferred. Experience in an academic/research background. If you think this opportunity could more »
similar role, with a strong emphasis on engineering Proficiency in Python programming and experience with relevant libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc. Extensive experience of deploying a cloud platform (GCP, AWS or Azure) Strong proficiency in NumPy for numerical computing and data manipulation tasks. more »
learning models and algorithms in real-world applications. - Strong proficiency in Python programming and popular machine learning libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Deep understanding of machine learning concepts and techniques, including supervised/unsupervised learning, deep learning, reinforcement learning, etc. - Strong communication and interpersonal more »
proven track record of deploying models in production settings. Advanced proficiency in Python and familiarity with machine learning and deep learning frameworks (e.g. Scikit-learn, PyTorch, TensorFlow). Experience with containerization technologies (e.g., Docker, ECR) and an understanding of GPU acceleration for deep learning. Expertise in a range more »
be valuable, but not essential: Experience with Azure Machine Learning, Cognitive Services, and Responsible AI Dashboard. Familiarity with shallow learning techniques using Python, Scikit-learn, XGBoost, etc. Exposure to deep learning frameworks like TensorFlow and PyTorch. Knowledge of various ML model deployment options, including real-time and batch more »
years in a managerial role overseeing a team of engineers. Proficiency in Python and experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of data science principles, predictive modelling, and advanced analytics. Excellent problem-solving skills and the ability to think critically and more »
associated security considerations. Previous experience with ML, LLM, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn is desirable. Experience in implementing secure coding practices, DevOps, CI/CD pipelines and familiarity with secure software development life cycle (SDLC) methodologies. more »
associated security considerations. Previous experience with ML, LLM, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn is desirable. Experience in implementing secure coding practices, DevOps, CI/CD pipelines and familiarity with secure software development life cycle (SDLC) methodologies. more »
SENIOR DATA SCIENTIST Customer & Marketing 💰£550 - £600 per day ⏰ 3 months + 🏠 Hybrid/London 📌Work across a range of clients in retail, telco, automotive and healthcare industries 📌Deliver a range of machine learning and AI solutions to support omnichannel more »
scientists Proficiency in data forecasting, analysis, prediction, and deriving trading signals from datasets. Extensive hands-on experience with TensorFlow (and/or Keras), scikit-learn, and related tools, coupled with a strong command of Python. Robust analytical and mathematical abilities essential for model development and validation. Exceptional problem more »
effectively. Technical Requirements To succeed in this role, you should have: Understanding of the full machine learning lifecycle and experience with frameworks like Scikit-learn, TensorFlow, or PyTorch. Demonstrable experience mentoring junior team members. Knowledge of probability, statistics, and common machine learning techniques. Experience in software engineering, particularly more »
Strong proficiency in programming languages commonly used in machine learning, preferably Python. Experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proven track record of developing and implementing machine learning solutions in a professional setting. Passion for exploring new technologies and more »
building and maintaining cloud Data Warehouses 2+ years’ experience of Snowflake configuration, deployment and maintenance Extensive hands-on experience of using Python commercially (scikit-learn, pandas, numpy, etc.) Extensive hands-on experience of using Azure to import, store, process and archive data If you feel your experience is more »
computer science or related field. Proven track record of peer-reviewed publications. Strong programming skills and experience working with Python and Pandas, Numpy, scikit-learn or other standard ML and deep learning libraries Familiar with commonly used machine learning algorithms and experience in using at least one deep more »
models. Experience in manipulating and interpreting data from disparate sources. Proficient in Python coding and core data science libraries, such as Pandas, TensorFlow, Scikit-learn etc. Experience with Cloud Computing (AWS, GCP, Azure) - Ideally in AWS. Creativity and innovative thinking to explore diverse data sources for improved predictive more »
deep understanding of its inner workings, including memory management, concurrency, and performance optimization. Proficiency in data science and machine learning libraries such as scikit-learn, TensorFlow, and PyTorch, with hands-on experience in developing and deploying machine learning models in production environments. Familiarity with financial markets and trading more »
Brighton, England, United Kingdom Hybrid / WFH Options
15gifts
based data science tech stack Python Docker & Kubernetes AWS Cloud Deep learning frameworks - Pytorch and Tensorflow HuggingFace ecosystem [optional] Other machine learning frameworks - scikit-learn, XGboost, CatBoost etc Ability to understand and develop state-of-the-art implementations Familiarity with state-of-the-art deep learning (e.g. transformers more »
the Influencer Marketing Awards 2022: “Industry Choice of SaaS or Technology” and “Best Influencer Marketing Technology” OUR DATA STACK: Our main technologies are: Python (ScikitLearn, Pandas, Numpy, Scipy) PostgreSQL Google Cloud KEY REMIT: Your responsibilities will fall across two areas: Creating algorithms and using existing technology to generate reports and more »
deploying machine learning models in a production environment - ideally in a start-up or scale-up. - Machine learning libraries and frameworks (TensorFlow, PyTorch, scikit-learn). - Python - Big data processing tools (e.g., Spark). The role offers a salary range of between £70-100K depending on experience. more »
s degree in Computer Science, Mathematics, or a related field Strong proficiency in Python and data science stack e.g. Pandas/Numpy/Scikit-learn Experience with data analysis and statistical modeling is a plus Excellent problem-solving skills and ability to work effectively under pressure Experience with more »
Senior level Data Scientist Solid knowledge of Data Engineering principles, including productionisation Technical experience with some or all of the following: Python, PySpark, scikit-learn, pandas, Azure Data Services, Databricks. If this sounds of interest, please apply. more »
knowledge of programming languages commonly used in AI development, such as Python, R, or TensorFlow. Experience with AI frameworks and libraries, such as scikit-learn, spaCy, or PyTorch. Solid understanding of data preprocessing, feature engineering, and model evaluation techniques in AI projects. Proficiency in integrating AI models with more »
correct manner -Must know CI/CD pipelines and Agile frameworks, preferably with the MLOps context. -Understanding or familiar with technologies such as: Scikit-Learn, TensorFlow, Torch, ChatGPT, Llama, LangChain (or equivalent), RAG, Model Security, Jupyter Notebook/JupyterLab, Unit Testing, Integration Testing, E2E Testing, ETL/ELT more »
