world applications Expertise with MLOps tools and practices (e.g., Docker, CI/CD pipelines, monitoring frameworks). Strong proficiency in Python and libraries like Pandas, NumPy, and scikit-learn, with familiarity in frameworks like TensorFlow or PyTorch being a plus Cloud experience—AWS preferred - including deploying and managing models in More ❯
skills in Python and SQL, with 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 More ❯
complex technical concepts to non-technical stakeholders. In-depth understanding of the Python software development stacks, ecosystems, frameworks and tools such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, sci-kit-learn and PyTorch Experience with popular Python frameworks such as Django, Flask or Pyramid Experience with Jupyter Notebooks Experience with More ❯
and guide this 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 More ❯
and guide this 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 More ❯
here. What you'll need Experience building, deploying and maintaining advanced Machine Learning models. Well versed in the scientific Python ecosystem (NumPy, Scikit-Learn, Pandas etc.) Strong Data Engineering underpinnings and an ability to work with big data (Tbs). Experience in at least one Deep Learning framework (PyTorch, TensorFlow More ❯
such as recommendation engines or automated lead scoring systems. They should also be able to perform statistical analysis. Requirements Python for DS (the usuals pandas plotting etc) Modelling skills for both ML applications and data reporting SQL at least basics but by year 3 should be quite proficient with at More ❯
using Python. Practical expertise and work experience with ML projects, both supervised and unsupervised. Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy datasets. More ❯
skills and a good understanding of software engineering principles and clean code practices. Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine More ❯
you will too What you'll need Strong knowledge of credit risk modelling. Strong experience in using Python for data processing across multiple libraries - Pandas, Polars, PySpark. Strong experience in the use of SQL for analytics and coding. Experience in use of MERIT (Model Execution Reporting and Insight Tool) as More ❯
Python for API and model development, including frameworks like Sklearn, Pytorch, and TensorFlow. Understanding of machine learning techniques. Experience with data manipulation libraries (e.g., Pandas, Spark, SQL). Experience with version control (Git). Cloud experience (Azure, GCP, AWS). Additional desirable skills include: Modeling experience in industry-relevant use More ❯
or similar. Technical knowledge of relevant ML performance metrics and how to apply them to monitor models. Strong knowledge of Python (such as numpy, pandas, matplotlib, streamlit, and opencv). Strong knowledge of modern programming paradigms (OOP, functional programming etc). Ability to write clean, robust, readable, error handling and More ❯
CD, version control (git), testing frameworks, MLOps Comfortable working with Docker and containerised applications Experience with data science Python libraries such as Scikit-learn, Pandas, NumPy, Pytorch etc. Experience using AWS or similar cloud computing platform Great communicator - convey complex ideas and solutions in clear, precise and accessible ways Team More ❯
solving and solution scoping Strong grasp of mathematical, statistical concepts, and machine learning algorithms Proficiency in Python and data science libraries for example NumPy, Pandas, Scikit-learn, Keras SQL proficiency Experience with cloud environments for example Google Cloud Platform Version control management Ability to work efficiently without compromising quality Effective More ❯
and guide this 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 More ❯
and guide this 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 More ❯
and guide this 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 More ❯
West Bend, Wisconsin, United States Hybrid / WFH Options
Delta Defense
PyTorch, TensorFlow, scikit-learn, and deep understanding of model lifecycle management. Strong command of the tools for building machine learning models. Proficient in Python (Pandas, NumPy, scikit-learn, PyTorch) and advanced SQL. 2 to 3 years of experience with big data platforms: Snowflake, Databricks or Spark. Solid understanding of probability More ❯
actionable insights. Capability to manage projects end-to-end and produce good outcomes without much supervision. Proficiency with data manipulation and modelling tools - e.g., pandas, statsmodels, R. Experience with scientific computing and tooling - e.g., NumPy, SciPy, R, Matlab, Mathematica, BLAS. Degree in Statistics, Mathematics, Physics or equivalent. Bonus: Experience implementing More ❯
actionable insights. Capability to manage projects end-to-end and produce good outcomes without much supervision. Proficiency with data manipulation and modelling tools - e.g., pandas, statsmodels, R. Experience with scientific computing and tooling - e.g., NumPy, SciPy, R, Matlab, Mathematica, BLAS. Degree in Statistics, Mathematics, Physics or equivalent. Bonus: Experience implementing More ❯
environments and HPC scheduling software. Software development including version control using GitWith open-source tools and software. Python and data analysis modules such as Pandas, NumPy, and Dask. Developing software in C/C++, Fortran or other programming languages. DESIRED QUALIFICATIONS In-depth understanding of HPC architectures and their optimization More ❯
