in Python with experience in C++ development Experience with Linux operating systems (e.g. Red Hat, Ubuntu) Experience with data analysis and manipulation tools (e.g. Pandas) Experience working across the Software Development Lifecycle (SDLC) Experience of using the Unified Modelling Language Excellent communication skills Desirable: Experience in the development of computer More ❯
Bristol, Stoke Gifford, Gloucestershire, United Kingdom
Synoptix
in Python with experience in C++ development Experience with Linux operating systems (e.g. Red Hat, Ubuntu) Experience with data analysis and manipulation tools (e.g. Pandas) Experience working across the Software Development Lifecycle (SDLC) Experience of using the Unified Modelling Language Excellent communication skills Desirable: Experience in the development of computer More ❯
development, job scheduling, and integration with other AWS services (e.g., S3, Glue). Proficiency in Python and experience with relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn) and Databricks-specific tools (e.g., Delta Tables, MLflow). Solid understanding of Machine Learning concepts and experience deploying models in production environments. More ❯
and machine learning fundamentals - either through a STEM degree, formal training, or self-study. Fluency in Python and SQL, including experience with libraries like Pandas, Scikit-learn, or equivalent. Demonstrated ability to solve real-world problems pragmatically using data. Clear, structured communication - especially the ability to explain complex topics simply. More ❯
a provider. Experience with different external data providers mainly SIX and Bloomberg Familiar with Oracle-DB, SQL and PL-SQL Familiar with Python and Pandas Experience in Unix System Management and JBoss Experience in Configuration Management and Deployment Automation especially with Bitbucket, Nexus, Jenkins, Octopus Familiar to work in an More ❯
requirements and restrictions Experience in programming languages and data structures such as SAS, Python, R, SQL is key. With Python background, particularly familiarity with pandas/polars/pyspark, pytest; understanding of OOP principles; git version control; knowledge of the following frameworks a plus: pydantic, pandera, sphinx Additionally, experience in More ❯
requirements and restrictions Experience in programming languages and data structures such as SAS, Python, R, SQL is key. With Python background, particularly familiarity with pandas/polars/pyspark, pytest; understanding of OOP principles; git version control; knowledge of the following frameworks a plus: pydantic, pandera, sphinx Additionally, experience in More ❯
of cyber security principles, including threat detection, incident response, and security operations. Technical Expertise: Proficiency in Python, SQL, and relevant data science libraries (e.g., pandas, scikit-learn, TensorFlow) and experience working with SIEM tools like Splunk and Elastic Search. Advanced Analytics & ML: Proven experience in applying machine learning techniques (anomaly More ❯
years Python work experience Any GUI development experience (Qt/PyQt would be ideal) Experience with Python data science libraries such as Pandas, Numpy, and Scipy XMIDAS familiarity C/C++ Code Management (Git would be ideal) Familiarity with the Atlassian tools (JIRA, Stash, Confluence, and Jenkins) and Gitlab Ability More ❯
some combination of Software Engineering, ML Engineering, Data Science, DevOps, and Cloud Infrastructure work. Expertise in Python which includes experience in libraries such as Pandas, scikit-learn. High proficiency in SQL. Knowledge of best practices in software engineering is necessary. Hands-on industry experience in some combination of the following More ❯
of SW development (3-5 Python) Any GUI development experience (Qt/PyQt would be ideal) Experience with Python data science libraries such as Pandas, Numpy, and Scipy XMIDAS familiarity C/C++ Code Management (Git would be ideal) Familiarity with the Atlassian tools (JIRA, Stash, Confluence, and Jenkins) and More ❯
experience with Oracle, SQL Server, and PostGres SQL databases. Technical Skills: Proficiency in at least 2 of the following: SQL, PSQL, C#, Python and Pandas for data manipulation and analysis. Problem Solving: Detail-oriented with exceptional problem-solving skills, capable of troubleshooting issues quickly and efficiently. Communication: Excellent ability to More ❯
/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or Pandas for high-performance data processing. Proficiency with cloud platforms (AWS, GCP, or Azure), including containerization and orchestration using Docker and Kubernetes. Hands-on experience with More ❯
experience with Oracle, SQL Server, and PostGres SQL databases. Technical Skills: Proficiency in at least 2 of the following: SQL, PSQL, C#, Python and Pandas for data manipulation and analysis. Problem Solving: Detail-oriented with exceptional problem-solving skills, capable of troubleshooting issues quickly and efficiently. Communication: Excellent ability to More ❯
skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid More ❯
back to technical and non-technical stakeholders through effective data visualisation and building of reporting frameworks Comfortable with Python data science libraries such as pandas, scikit-learn, numpy, statsmodels Strong SQL experience including analytic functions, performance tuning, data wrangling Ability to work collaboratively and proactively in a fast-paced environment More ❯
probabilistic models, clustering algorithms, classification models and time series techniques in a production environment. Proficiency with Python and all related Data Science libraries (numpy, pandas, matplotlib, etc.), and SQL with excellent analytical and algorithmic skills. A proven record for successful implementation of translating business requirements into a technical solution. Multi More ❯
skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid More ❯
skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid More ❯
/or geospatial analytics Proven ability to analyze data and translate analysis into meaningful insights Comfortable with standard ETL and data cleansing processes in pandas or similar Proficiency in one or more programming languages, preferably including Python Demonstrated ability to manipulate large data sets into user-friendly formats for stakeholder More ❯
in a dynamic, fast-paced environment; retail focus preferred. You have experience extracting data from databases using SQL and analysing data using Python (NumPy, Pandas, etc.). You have a bachelor degree in a quantitative subject. You are capable of acting as a trusted advisor when presenting data and insights More ❯
the ability to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid More ❯
Understanding of LTV modeling, forecasting, and experimental design. Comprehension of A/B testing methodologies Proficiency in Python for data analysis and modeling (e.g., pandas, scikit-learn, statsmodels). Strong SQL skills and experience working with large datasets in modern data environments. Experience working with cross-functional growth or marketing More ❯
dynamic network analysis). Expertise in maintaining and deploying a notebook-based data science environment (JupyterHub). Experience in advanced Python data science packages (Pandas, NetworkX, Scikit-Learn, PyTorch or TensorFlow/Keras, Matplotlib or Plotly, etc.) _ Compensation ranges encompass a total compensation package and are a general guideline only More ❯
