276 to 300 of 445 scikit-learn Jobs

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science - scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large "Big Data" environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large Big Data environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision More ❯

and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision More ❯

and mentoring a team of talented data scientists. What You'll Bring Deep expertise in machine learning and statistical modelling ️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) Experienced project lead with strong technical decision More ❯

applications, and mentoring a team of talented data scientists. What Youll Bring Deep expertise in machine learning and statistical modelling Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) Experienced project lead with strong technical decision More ❯

applications, and mentoring a team of talented data scientists. What Youll Bring Deep expertise in machine learning and statistical modelling Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) Experienced project lead with strong technical decision More ❯

and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision More ❯

business narratives Contributing to simple, reliable data pipelines and automated quality checks About You Minimum 1 year of commercial Data Science experience Strong hands-on Python (pandas, NumPy, scikit-learn) and SQL Sound understanding of statistics and forecasting Confident communicator - able to explain technical work clearly to non-technical audiences Why Apply Opportunity to build from scratch within More ❯

a senior data science role. Deep understanding of machine learning model lifecycles and optimisation. Skilled in building, training, and deploying models on large datasets. Proficiency in Python, PyTorch, Scikit-learn, and similar ML frameworks. Experience with cloud environments (AWS preferred), containerisation, and modern data infrastructure. Excellent communication skills, with the ability to work effectively across technical and non More ❯

others. Knowledge of AWS or similar cloud providers. Understanding Software Engineering techniques and processes. Strong interpersonal, communication, and presentation skills applicable to a wide audience. Knowledge of PyTorch, Scikit-learn, Azure Pipelines, Databricks, and AWS CDK is desirable, but not essential. Experience of participation in software engineering efforts for AI-enabled SaaS products is desirable, but not essential.Join More ❯

in the job offered or a related position. Experience must include demonstrable knowledge of: deep learning models for segmentation/classification using medical imaging; Python; SQL; typescript; PyTorch; scikit-learn; OpenCV; PIL; pydicom; matplotlib; seaborn; SHAP; Grad-CAM; AWS; Fast API; Kubernetes; PostgreSQL; Snowflake; MongoDB; OpenAI API; Git; GitHub; Slack, and SaMD principles. Required knowledge may be acquired More ❯

Server, Snowflake, Redshift, Presto, etc Experience building ETL and stream processing pipelines using Kafka, Spark, Flink, Airflow/Prefect, etc. Familiarity with data science stack: e.g. Juypter, Pandas, Scikit-learn, Dask, Pytorch, MLFlow, Kubeflow, etc. Strong experience with using AWS/Google Cloud Platform (S3S, EC2E, IAM, etc, Kubernetes and Linux in production Strong proclivity for automation and More ❯

in how you design solutions and test what's working - always with an eye on practical outcomes. Hands-on technical skills: Strong Python, confident with ML libraries like scikit-learn, pandas, and LightGBM. You've worked with cloud infrastructure (e.g. GCP) and modern data tools (e.g. dbt, Snowflake). Cross-collaboration: You thrive in highly collaborative environments, communicate More ❯

and system integrations. Strong knowledge of data pipeline design, security best practices, and microservice architectures. Hands on experience with Python and machine learning frameworks such as TensorFlow, PyTorch, Scikit learn, or JAX. Familiarity with tools like Apache Airflow, Snowflake, dbt, or custom ETL stacks for data pipeline implementation. Ability to collaborate with scientific and machine learning teams to More ❯

years in data science, with at least 2 years in a leadership role managing teams and projects. Technical Skills : Proficiency in Python, SQL, and machine learning libraries (e.g., scikit learn, TensorFlow, PyTorch). Strong knowledge of cloud environments and services (AWS, Google Cloud). Domain Knowledge : Experience in credit risk modeling, fraud detection, or financial services is highly More ❯

and explore practical applications of AI. Overview of AI and Machine Learning Types of machine learning (supervised, unsupervised, reinforcement) Introduction to Python Libraries for AI - NumPy, Pandas, Matplotlib Scikit-learn for machine learning Building AI Models Data preprocessing Training and evaluating models Advanced Programming for AI Integration This programme aims to equip participants with the knowledge and practical More ❯

NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant tools & mathematical background • Docker, Kubernetes, AWS 📍 Location : London (1 remote day per week) 💼 Type : Full-time | Competitive comp + performance bonus Ready to build systems that More ❯

NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant tools & mathematical background • Docker, Kubernetes, AWS 📍 Location : London (1 remote day per week) 💼 Type : Full-time | Competitive comp + performance bonus Ready to build systems that More ❯

NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant tools & mathematical background • Docker, Kubernetes, AWS 📍 Location : London (1 remote day per week) 💼 Type : Full-time | Competitive comp + performance bonus Ready to build systems that More ❯

methods using the latest AI and data science tools. The ideal candidate will have hands-on experience applying and deploying machine learning and AI tools like Python, TensorFlow, scikit-learn, or similar, to commercial pricing problems. Strong communication skills, modelling ability, and familiarity with data visualisation tools such as Power Bi or tableau is essential. The company offers More ❯

NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant tools & mathematical background • Docker, Kubernetes, AWS 📍 Location : London (1 remote day per week) 💼 Type : Full-time | Competitive comp + performance bonus Ready to build systems that More ❯