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 »
Analytical background, as evidenced by a STEM degree in a technical subject Competencies in Python and the Python data science ecosystem (pandas, numpy, scikit-learn etc.) or highly transferable skill analogues Experience developing and evaluating models using at least one of the following technologies: —- Gradient-boosted decision trees 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 »
concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This is a pragmatic more »
of timely project delivery. Strong programming, statistics, mathematics, and ML algorithm fundamentals, with Python expertise. Familiarity with ML/DS frameworks (e.g., XGBoost, Scikit-learn) and modern OOP practices. Proficient in development best practices and version control (e.g., Git). Knowledgeable in memory, disk I/O, and more »
a 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 concepts 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 »
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 »
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. The 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 »
models and algorithms.Strong proficiency in programming languages such as Python, R, or Java, and familiarity with libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, and Spark.Solid understanding of statistical analysis, data mining, and predictive modeling techniques.Experience with big data technologies such as Hadoop, Spark, and distributed computing more »
Borehamwood, England, United Kingdom Hybrid / WFH Options
Addition+
processing, and stream processing. Experience with or at least an interest in Machine Learning and widely used technologies, such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, and PyTorch. Knowledgeable about key MLOps concepts such as CI (including data aspects), CD (specific to ML), CT (Continuous Training), feature stores 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)PostgreSQLGoogle CloudKEY REMIT:Your responsibilities will fall across two areas:Creating algorithms and using existing technology to generate reports and insight more more »
years experience in software engineering or data science with a focus on machine learning Experience in the python library - Pytorch, Pandas, Numpy, Tensorflow, Scikit-learn Experienced working in a microservice-based architecture# Experience working with Docker or Kubernetes Strong interest in ML and keeping up to date with more »
methods, optimizers, super/unsupervised learning, feature engineering, etc.). Strong experience with Python required understanding of the ML/DS frameworks (XGBoost, Scikit-learn, Pandas, Numpy, etc.), and modular/modern OOP software design practices with a modern ML/Data/Cloud engineering technical stack If more »
based methods, optimizers, super/unsupervised learning, feature engineering, etc.). Strong experience with Python requiredunderstanding of the ML/DS frameworks (XGBoost, Scikit-learn, Pandas, Numpy, etc.), and modular/modern OOP software design practiceswith a modern ML/Data/Cloud engineering technical stackIf you’re more »
concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This is a pragmatic more »
sources and explore novel methodologies to uncover groundbreaking insights. Required Skills: Proficient in Python 3 and popular data science tools such as pandas, scikit-learn, and more. Extensive experience in creating and fine-tuning machine learning models. Knowledge of time series forecasting and optimisation techniques for accurate predictions. more »
development, and deployment of complex machine learning solutions.Expertise in product experimentation, Causal AI, and advanced statistical techniques.Deep knowledge of data science tools (e.g., scikit-learn, TensorFlow, PyTorch) and big data technologies (e.g., Spark).Proficiency in Python for data manipulation, model building, and scripting.Strong communication skills to present findings more »
design, security, and deployment Understanding of and interest in the full machine learning lifecycle, including deployment of trained ML models using common frameworks (Scikit-learn, TensorFlow, PyTorch) and ideally Azure managed ones (Azure ML Workspace, Azure ML Studio) Experience in Software Engineering including programming and development of applications more »
deployment of complex machine learning solutions. Expertise in product experimentation, Causal AI, and advanced statistical techniques. Deep knowledge of data science tools (e.g., scikit-learn, TensorFlow, PyTorch) and big data technologies (e.g., Spark). Proficiency in Python for data manipulation, model building, and scripting. Strong communication skills to more »
design, security, and deployment Understanding of and interest in the full machine learning lifecycle, including deployment of trained ML models using common frameworks (Scikit-learn, TensorFlow, PyTorch) and ideally Azure managed ones (Azure ML Workspace, Azure ML Studio) Experience in Software Engineering including programming and development of applications more »
within financial services (ideally within financial crime prevention based projects) Very Strong Python skills and strong familiarity with the data science stack (pandas, scikit-learn and network) Have experience working in a, dynamic and scientific manner and creating high-quality models Be able to effectively explain complex technical more »
