Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity: Generous equity package, on a standard vesting schedule Impact & Exposure: Work More ❯
Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience. Equity: Generous equity package, on a standard vesting schedule. Impact & Exposure: Work More ❯
models is a plus. Experience in building, validating, and deploying predictive models, ensuring they meet business objectives. Experience with data visualization tools such as Matplotlib, Tableau, Plotly, Dash. Familiarity in leveraging automation and AI tools for coding and writing purposes is a plus. Analytical & Problem-Solving Skills: Ability to work More ❯
Azure). Experience building APIs for AI/ML models using FastAPI, Flask, or similar frameworks. Proficiency in data visualization tools (Looker, Streamlit, Plotly, matplotlib, etc.). Knowledge of MLOps best practices for deployment, monitoring, and model lifecycle management. Knowledge of general CI/CD best practices Experience with Docker More ❯
Learning methods, Statistics). Fluent in common analytics tools (Python, Pandas, Numpy, ScikitLearn, SQL, etc.). Comfortable to use data visualization libraries (e.g. Seaborn, Matplotlib). Demonstrated initiative, judgment and discretion while handling sensitive information. Preferred Qualifications If you have the following characteristics, it would be a plus: PhD - in More ❯
the ability to query databases and manipulate large datasets. Proficiency in key Python libraries for data science, including Pandas, Scikit-learn, Statsmodels, NumPy, SciPy, Matplotlib, TensorFlow, and Keras. Solid understanding of machine learning techniques, such as clustering, tree-based methods, boosting, text mining, and neural networks. Expertise in statistical modeling More ❯
and modern Deep Learning algorithms (e.g., BERT, LSTM, etc.) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib, etc.) Understanding of model evaluation, data pre-processing techniques, such as standardisation, normalisation, and handling missing data Solid understanding of summary, robust, and nonparametric statistics More ❯
fundamentals (Machine Learning methods, Statistics). Fluent in common analytics tools (Python, Pandas, Numpy, ScikitLearn, SQL, etc.) Comfortable using data visualization libraries (e.g. Seaborn, Matplotlib) Demonstrated initiative, judgment and discretion while handling sensitive information Preferred Qualifications: If you have the following characteristics, it would be a plus: PhD in a More ❯
and modern Deep Learning algorithms (e.g. BERT, LSTM, etc) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib, etc) Understanding of model evaluation, data pre-processing techniques, such as standardisation, normalisation, and handling missing data Solid understanding of summary, robust, and nonparametric statistics More ❯
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-tasking More ❯
working with large-scale datasets and utilizing big data technologies (e.g., Azure, Databricks, Spark) Familiarity with data visualization tools such as Power BI, or matplotlib Strong knowledge of predictive modeling, machine learning techniques, and statistical analysis. Soft Skills Analytical mindset with a passion for uncovering actionable insights from complex datasets. More ❯
the pharmaceutical industry preferred. Strong proficiency in programming languages such as Python, R, or MATLAB, and relevant data science libraries (such as NumPy, Pandas, Matplotlib, Scikit-learn, etc.) for data analysis, manipulation, and visualization. Experience with bioinformatics tools and databases, especially those pertinent to omics data analysis such as Squidpy More ❯
the pharmaceutical industry preferred. Strong proficiency in programming languages such as Python, R, or MATLAB, and relevant data science libraries (such as NumPy, Pandas, Matplotlib, Scikit-learn, etc.) for data analysis, manipulation, and visualization. Experience with bioinformatics tools and databases, especially those pertinent to omics data analysis such as Squidpy More ❯
record of deploying ML models to production. A good command of analytical programming and visualisation languages and libraries (SQL, Python and/or R, matplotlib/ggplot etc.) as well as supporting tools and platforms (e.g. git, Sagemaker, VS Code). A strong understanding of statistical concepts (hypothesis testing, sampling More ❯
collaborating with team members. Knowledge of CI/CD pipelines (e.g. GitHub Actions) is a plus. Experience with data visualization tools and libraries (e.g., Matplotlib, Seaborn, Tableau, Power BI). Experience with cloud services (e.g., AWS, Google Cloud Platform, Azure) for data storage and processing. Ability to work with cross More ❯
on experience in data science, business intelligence, and reporting. Experience in the core Python libraries used for in data science, including Pandas, Numpy, and Matplotlib is essential. Strong understanding of statistical concepts and analytics/machine learning techniques, including regression, classification, clustering, NLP, and dimensionality reduction. Experience with Azure Cloud More ❯
business needs and translate them into data-driven solutions. Create insightful visualizations and dashboards using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn) to communicate findings effectively to non-technical stakeholders. Continuously evaluate and improve the performance of models through cross-validation, hyperparameter tuning, and other techniques. … data manipulation and transformation tools such as Pandas, NumPy, and SQL for working with large datasets. Expertise in creating impactful visualizations using tools like Matplotlib, Seaborn, Tableau, or Power BI. Familiarity with big data tools and platforms like Hadoop, Spark, or cloud-based tools (e.g., AWS, Google Cloud, Azure). More ❯
developing and deploying machine learning models in production. Strong programming skills in Python and SQL. Proficiency with data visualization tools (e.g., Tableau, Power BI, matplotlib) and cloud platforms (preferably AWS). Expertise in statistics and machine learning frameworks (e.g., PyTorch, scikit-learn). Familiarity with Git and collaborative workflows, such More ❯
including issue/workflow tracking tools like Jira and Trello, and version control tools like git and GitHub Experience with visualizing data using ggplot2, matplotlib, d3.js, Tableau, or similar software #J-18808-Ljbffr More ❯
a team with fast turnarounds, manage workloads effectively and readily assume additional responsibilities Exposure to data analysis libraries (e.g., pandas, numpy) and visualisation tools (Matplotlib, plotly) Understanding software testing principles and frameworks Preferred skills Knowledge of financial instruments and equity markets Familiarity with cloud services Familiarity with quantitative research methodologies More ❯
Create visually appealing and interactive charts, graphs, and dashboards to represent data analysis results. Use tools like Tableau, Power BI, or Python libraries like Matplotlib or Seaborn. Problem-Solving: Identify business problems or challenges and formulate data-driven solutions. Collaborate with cross-functional teams to understand requirements and provide analytical More ❯
support the integration and application of data science approaches Desired requirements for the role are: Experience working with sophisticated data visualisation libraries such as Matplotlib and Plotly in Python Experience in a consultancy role Experience with data science related tools (e.g. Shiny, D3, AWS, dbt) Experience with statistical/analytical More ❯
£2.5 million seed funded Startup utilising Machine Learning
and React on the Frontend. Tech & Data Science stack: Kubernetes & Docker on Google Cloud Python 3: Pandas, RabbitMQ, Celery, Flask, SciPy, NumPy, Dash, Plotly, Matplotlib Javascript, React, Redux PostgreSQL, Redis Prometheus, Alert Manager, DataDog If you joined the company in a Data Science role you would be working on sophisticated More ❯
sklearn, spaCy, NumPy, SciPy etc.). Experience using Git for version control and familiarity with CI/CD pipelines. Comfortable with data visualisation tools (Matplotlib, Seaborn etc.). Experience using cloud platforms (AWS, GCP, Azure) for ML pipelines. Strong communication skills - able to explain technical details to non-technical stakeholders. More ❯
work through others. Experienced in using Python and SQL to query and analyse large datasets, with expertise in libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a More ❯
