76 to 100 of 180 Pandas Jobs

data concepts effectively and confidently Build great relationships with Data Science, Technology, Finance, Collections, Ops and other stakeholders What you'll need Excellent SQL skills Python data science stack (pandas, NumPy, Jupyter notebooks, Plotly/matplotlib, etc) A drive to solve problems using data Experience in a management role What would be a bonus: Familiarity with Git Data visualization tool More ❯

in statistical modeling. Experience with Power BI, Power Query, Power Automate, Power Apps, MS Excel, Python, and SQL. Experience using Python or R packages and libraries (e.g., scikit-learn, pandas, plotly, shiny, etc.) to develop predictive analyses and machine learning models. Preferred Experience: Preferred: Experience with cloud computing/storage, data lakes/warehouses. Preferred: Experience with Spark and ML More ❯

create compelling data visualizations using products like Tableau, Microsoft Power BI, and R Shiny Research, design, and implement algorithms to solve complex problems Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages Perform data engineering, data processing, and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and More ❯

create compelling data visualizations using products like Tableau, Microsoft Power BI, and R Shiny Research, design, and implement algorithms to solve complex problems Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages Perform data engineering, data processing, and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and More ❯

in computer science , 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 More ❯

SaaS or usage based preferred). Deep hands on expertise withdbt(production grade models, testing, CI/CD) andSnowflake(performance tuning, RBAC, cost management). Advanced SQL + Python (pandas, scipy/statsmodels, or Prophet) for forecasting, scenario modeling, and statistical analysis. Strong grasp of SaaS/cloudunit economics-MRR/ARR, COGS allocation, gross margin, payback, LTV/CAC More ❯

science and advanced analytics to generate business value and change, including optimisation of production processes Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) is required; Familiarity with PySpark is also desirable. A cloud platform experience (e.g Azure, AWS, GCP), we're using Azure in the team. Good SQL understanding More ❯

concepts and influence decisions. Comfortable working with imperfect data, ambiguity, and evolving priorities. Bonus: experience with DBT, cloud data warehouses (e.g. BigQuery), or automated experimentation platforms. Technology Python (incl. pandas, statsmodels, scikit-learn), Jupyter dbt, SQL (BigQuery, PostgreSQL) Tableau or similar BI tools GitHub, GCP, Docker (optional but useful) How we expect you to work ️ Collaboration : We work in cross More ❯

Experience 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. More ❯

record 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. 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 ❯

related 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 More ❯

Well-versed in Python. Strong team player. Strong communication skills. Software Developer tech stack: Python > 3.5 with type hints, data classes, and Flask REST API. Postgres for relational data, Pandas for data analysis, and Google Cloud Pub/Sub for messaging. Cloud Build for automated builds, and Cloud Run/Docker for containerisation. Google Cloud Platform is used for infrastructure. More ❯

managing risk in EMEA markets Proven trading track record of systematic trading profitability & understanding of common systematic trading strategies Fluency in quantitative data analysis using latest tools, preferably python, pandas & KDB Organizational and time management skills Strong communication, both real-time & technical communication This role encompasses the performance of UK regulated activity. The successful candidate will therefore be subject to More ❯

Washington 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 More ❯

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 passion More ❯

Work 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 More ❯

types and structures Unit testing using pytest Proficiency in SQL (we use MySQL, but experience with other SQL platforms is welcome). Experience with data manipulation and transformation using Pandas . Familiarity with ETL/ELT processes and data warehousing concepts. Understanding of cloud platforms (AWS or Azure). Basic knowledge of Git and GitHub for version control and collaboration. More ❯

types and structures Unit testing using pytest Proficiency in SQL (we use MySQL, but experience with other SQL platforms is welcome). Experience with data manipulation and transformation using Pandas . Familiarity with ETL/ELT processes and data warehousing concepts. Understanding of cloud platforms (AWS or Azure). Basic knowledge of Git and GitHub for version control and collaboration. More ❯

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 chat More ❯

degree 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 More ❯

systems (e.g. Red Hat, Ubuntu) Experience working within a variety of development frameworks and practices e.g. DevOps, DevSecOps, SCRUM, MLOps, XP. Experience with data analysis and manipulation tools (e.g. Pandas) Experience of a broad section of the Software Development Lifecycle (SDLC) with specific focus on: Design(Architecting, High-Level Design and Low-Level Design) Development Testing Deployment & Maintenance Experience of More ❯

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 leading More ❯

will then proceed to the Customer python screening, and the Customer ML interview. May not use AI LLMs during code screens. Candidates must have extreme fluency in numpy and pandas More ❯

accuracy. 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 More ❯