101 to 125 of 193 NumPy Jobs

with neural deep learning methods and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD in math/statistics/engineering or other equivalent quantitative discipline - Experience with conducting research in More ❯

learning - Experience in building machine learning models for business application - Experience in applied research PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central More ❯

Mathematics, Statistics, Business Administration or related field Advanced knowledge of SQL (joins, aggregations, CTEs and window functions) Good knowledge of Python, including popular Data Science packages (pandas, matplotlib, seaborn, numpy , sklearn ) Familiarity with what is happening under the hood of popular Machine Learning algorithms Strong problem-solving skills and attention to detail Strong communication and collaboration skills Ability to work More ❯

PhD degree in a quantitative field. Proven experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with the ability to present complex data insights to More ❯

experience in designing, developing & deploying scalable backend systems. Familiarity with CICD, containerisation, deployment technologies & cloud platforms (Jenkins, Kubernetes, Docker, AWS) or Familiarity with Big Data and Machine Learning technologies (NumPy, PyTorch, TensorFlow, Spark). Excellent communication, collaboration & problem solving skills, ideally with some experience in agile ways of working. Security clearance: You must be able to gain and maintain the More ❯

data analytics including statistics, data visualization, and working with large data sets Basic understanding of TCP and UDP network protocols Extensive experience with Python and relevant data libraries (Pandas, Numpy/Scipy) Some familiarity with the details of modern computer systems and networks Experience with real time exchange market data and order entry a plus Profile You possess a degree More ❯

similar role. Strong programming 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 learning libraries like scikit-learn, PyTorch More ❯

delivering data science or data engineering solutions into production. You're comfortable writing production-grade code, not just notebooks. Strong Python and SQL skills, including the basic libraries (Pandas, Numpy, ScikitLearn). You value writing clean, maintainable, and tested code. Proven ability to design, build, and maintain data pipelines and tools from scratch that are reliable, maintainable, and scalable. Strong More ❯

technical teams Direct experience working with social and digital platforms such as Meta, Amazon, Google to onboard datasets an advantage Proficiency working with data in SQL and Python (Pandas, NumPy preferred) Knowledge of statistical testing methodologies Experience with BI tools (Tableau, PowerBI preferred) Experience with cloud computing services & solutions (AWS, Azure, GCP, Amazon Marketing Cloud, Snowflake) Experience working with very More ❯

of leading high-performing teams. Proven ability to build predictive models and extract insights from large, complex datasets. Advanced proficiency in Python and SQL, including libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn. Skilled in developing and deploying credit risk models, including scorecard thresholds, limit optimisation, and loss reduction. Experience with Monte Carlo simulations or Bayesian modelling (e.g., PyMC3 More ❯

programming skills in SQL, SAS (desired), Python, and the ability to write production-level code Familiarity with the most standard Python libraries used in ML (e.g., Scikit-Learn, Pandas, Numpy, LightGBM, XGBoost, just to name a few) Foster new and innovative machine-learning techniques and approaches General: Passionate for continuous learning, experimenting, and applying open-source technologies within the machine More ❯

Can Excel in This Role Strong python development experience, able to follow PEP8 standards Experience of developing GIS pipelines in python, leveraging open source libraries such as Fiona, Shapely, Numpy and Rasterio Ability to communicate effectively, explaining and rationalizing design decisions to a cross functional team. Experience in object-oriented programming concepts, unit & integration testing, data and relational databases, technical More ❯

Vertex Pipelines (or similar platforms). Technical Proficiency: in SQL and Python, along with familiarity with standard libraries used in data science such as scikit-learn, Keras, TensorFlow, pandas, NumPy, seaborn, and Matplotlib. Desirables: While not essential, the following experience would be highly beneficial: Production Experience with LLM Monitoring: Hands-on experience with monitoring LLMs in production, including familiarity with More ❯

methodologies About you We don't expect perfection, but for this senior role we are looking for someone with: Strong Python skills, particularly within the data science ecosystem (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow, visualisation libraries) 4+ years of experience delivering machine learning products end-to-end in production Hands-on experience with LLMs - fine-tuning, prompt engineering, vector More ❯

Top Skills: - Python - Machine Learning - JavaScript - Numpy and Pandas is a plus - This position requires an active DoD Clearance (Secret, Top Secret, Top Secret/SCI) or the ability to be obtain an (Interim Secret, Interim Top Secret) - Because an active or interim DoD clearance is required, U.S. Citizenship is required Eligibility requirements apply to some benefits and may depend More ❯

to credit risk management. • 2+ years of experience as a quantitative researcher or data scientist. • Strong programming skills in Python and experience with data science tools such as Pandas, NumPy, and SciPy. • Strong statistical and modeling skills. • Strong communication and collaboration skills. • Experience in the energy industry is a plus. Competitive salary and a stock options sign-on bonus Biannual More ❯

DC/Northern Virginia with occasional travel to client sites. A degree in Computer Science or a related field. 3+ years of hands-on experience with Python coding (pandas, numpy, sklearn, TensorFlow, PyTorch, etc.). Proven experience deploying machine learning models into production environments. Proficiency with SQL/NoSQL databases, version control tools (e.g., Git), Docker, and Kubernetes. Strong ownership More ❯

again, and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong communication skills and a More ❯

with other data scientists to build and deploy production-level solutions Troubleshoot and debug code Work with other teams to understand and solve business problems About you: Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine More ❯

of. • 5+ years of Data Science development experience using Python • Proficiency in data science, machine learning, and analytics, including statistical data analysis, model and feature evaluations. • Strong proficiency in numpy & pandas. • Demonstrated skills with Jupyter Notebook or comparable environments • Practical experience in solving complex problems in an applied environment, and proficiency in critical thinking. • Candidates require a TS to start. More ❯

a cross-functional environment with other data scientists, software engineers, and T&L domain experts Your professional experience Essential: Expert Python programmer proficient in frameworks/libraries such as: Numpy, Pandas, Scikit-Learn, Langchain, Llamaindex, Azure AI Foundry, among others Practical experience and deep expertise with GenAI techniques such as Finetuning, Prompt engineering, prompt orchestration, retrieval methods (RAG and Knowledge More ❯

better Ideally experience with de novo transcriptome assembly, Machine Learning and/or Artificial Intelligence, or experience mining genomic data Experience with Python and libraries such as SciPy, Pytorch, NumPy, Pandas etc. What Next? If you'd like to hear more about this exciting Bioinformatician position, just give me a call or drop me an email, I'd love to More ❯

in Computer Science (or related field). 3+ years of experience writing production-grade Python code. 3+ years of hands-on experience with core Python data libraries (e.g., pandas, numpy, sklearn, tensorflow, pytorch, matplotlib). At least 1 year of experience deploying machine learning models in production environments. 1-2 years of experience working with SQL/NoSQL databases (e.g. More ❯

level experience in data science or a quantitative academic field. Strong programming skills, with the ability to quickly become fluent in Python. Deep knowledge of core data science libraries (NumPy, Pandas, Scikit-Learn) and at least one deep learning framework (TensorFlow, PyTorch, or similar). High mathematical and statistical competence, with the ability to design new algorithms when needed. Experience More ❯

Requirements: 5+ years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and More ❯