16 to 40 of 191 Pandas Jobs

professional experience in data science or machine learning, ideally in fintech, financial services, or a B2B2C environment Strong proficiency in SQL and Python (pandas, scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) Hands-on experience with tree-based models (XGBoost, LightGBM, CatBoost) and neural networks Proficiency in notebooks (Jupyter, Colab, etc. ...

Python and SQL, with plenty of familiarity using popular libraries for machine learning (e.g. scikit-learn, XGBoost, LightGBM, PyTorch) and data manipulation (e.g. Pandas, NumPy, Polars, DuckDB, Dask). Experience applying software engineering best practices to both greenfield and brownfield development (e.g. testing, CI/CD, containerization, observability) Excellent technical ...

also open to candidates from other asset classes with genuine interest in power & gas. Strong Python skills and experience with the scientific stack (NumPy, pandas, SciPy, scikit-learn or similar). You write clean, production-grade code, not just notebooks. Solid understanding of stochastic processes, Monte Carlo simulation, and time ...

also open to candidates from other asset classes with genuine interest in power & gas. Strong Python skills and experience with the scientific stack (NumPy, pandas, SciPy, scikit-learn or similar). You write clean, production-grade code, not just notebooks. Solid understanding of stochastic processes, Monte Carlo simulation, and time ...

also open to candidates from other asset classes with genuine interest in power & gas. Strong Python skills and experience with the scientific stack (NumPy, pandas, SciPy, scikit-learn or similar). You write clean, production-grade code, not just notebooks. Solid understanding of stochastic processes, Monte Carlo simulation, and time ...

also open to candidates from other asset classes with genuine interest in power & gas. Strong Python skills and experience with the scientific stack (NumPy, pandas, SciPy, scikit-learn or similar). You write clean, production-grade code, not just notebooks. Solid understanding of stochastic processes, Monte Carlo simulation, and time ...

turn abstract business and product ideas into concrete data science and engineering solutions. Expert-level coding abilities in Python for data science (e.g., Pandas, NumPy, Scikit-learn) and mastery of complex SQL across large datasets. Ability to effectively communicate complex technical concepts to both technical and non-technical audiences. Desire ...

turn abstract business and product ideas into concrete data science and engineering solutions. Expert-level coding abilities in Python for data science (e.g., Pandas, NumPy, Scikit-learn) and mastery of complex SQL across large datasets. Ability to effectively communicate complex technical concepts to both technical and non-technical audiences. Desire ...

Models (GPT, Claude), Generative AI, RAG Agentic AI, CoPilot, MCPs AIML Algorithms (Regression, Classification, Decision Trees, KNN, K-Means) Python (NLTK, NumPy, Scikit-learn, Pandas) Experience building AIML solutions for test generation, prioritization, defect triage, reporting, framework migration Strong understanding of QA automation frameworks and test lifecycle SQL proficiency Agile ...

researchers to design pipelines for modeling and back-testing. Document and maintain the firm’s core data architecture. Requirements: 5+ years of Python development (Pandas, SQL, Linux environment). Hands-on experience building data solutions for trading, research, or risk. Deep technical curiosity and strong problem-solving skills. Strong knowledge ...

data extraction and manipulation. Experience working with large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling ...

M.S. or Ph.D. in a related field highly desired 5+ years of experience with machine learning, statistical modeling, and optimization techniques Fluent in Python (pandas, numpy, SciPy, and scikit-learn preferred) Proficient in linear algebra and statistics Familiar with scientific software principals, e.g. versioning systems, reproducibility Experience in the manufacturing ...

Computer Science, Engineering, or a related field 5+ years of experience as a Data Engineer or a similar role Strong proficiency in Python, Pandas, and SQL Experience with AWS technologies such as Lambdas, Step Functions, Redshift, S3, Athena, Glue, and Kinesis Familiarity with data cleaning, processing, and analytics of image ...

supervised and unsupervised learning, natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ? Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) ? Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks. ? Experience with ML Ops, including model deployment ...

applied mathematics, or a related field. Experience with AI frameworks (e.g., TensorFlow, PyTorch, scikit-learn, OpenCV). Familiarity with tools such as NumPy, SciPy, Pandas, Matplotlib. Experience deploying AI models in cloud environments (e.g., AWS, Azure). Strong analytical skills and creative problem-solving ability. Understanding of Agile development methodology. ...

familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability ...

data models, and performing schema migrations. Demonstrable thought leadership on operationalizing data quality Development experience delivering production ready code in Python. Familiarity with Pandas framework. Strong collaborator across functional areas, incl. data science, infrastructure, software development, and product Preferred Experience Hands on knowledge of GIS enabled data stores such ...

PyTorch, or TensorFlow for model development. AWS Bedrock, Sagemaker, HuggingFace, or equivalent cloud AI stacks. CrewAI or other orchestration frameworks for agentic AI systems. Pandas, NumPy, Airflow, or Databricks for data engineering and workflow automation. Understanding of model lifecycle management, including monitoring, retraining, and versioning. Experience influencing architecture and tooling ...

Expertise in causal inference with observational and experimental data. Strong engineering skills with expertise in R or Python and fluency in data manipulation (SQL, Pandas) and machine learning (scikit-learn, XGBoost, Keras/Tensorflow) tools. An ability to identify and prioritize high-impact problems and deliver solutions that provide reasonable ...

/Analytics: Mixpanel, Explo Languages: Python, SQL Version Control: Git AI/ML Stack LLM Frameworks: Anthropic, OpenAI, Google LangChain Data Science & ML Libraries: pandas, scikit-learn NLP Tools: Hugging Face Nice to Have Experience with Node.js/TypeScript Background in conversation AI or natural language processing ...

architectures, optimizers, statistical principles) and the data science lifecycle. Strong proficiency in Python's scientific computing and Machine Learning ecosystem (e.g., PyTorch, NumPy, SciPy, Pandas). An understanding of how high-level Machine Learning frameworks interact with low-level hardware (e.g., C CUDA on GPUs). A proactive ownership mindset ...

years of experience delivering production-quality software with increasing levels of ownership and technical leadership. Fluent in Python and expertise with libraries like NumPy, Pandas, and scikit-learn Strong background in statistical analysis and computational mathematics with first principles knowledge of machine learning techniques Fundamental understanding of modern AI/ ...

/B test evaluation, with a clear understanding of sampling, control groups, and significance testing in applied business contexts Demonstrated expertise in Python (pandas, numpy, scikit-learn, etc.) and SQL, with the ability to design efficient data pipelines and feature engineering workflows Strong background in data exploration, feature engineering ...

cloud-native model training and deployment, model serving, and effective data lifecycle management. Expert proficiency in Python, SQL, and core ML libraries (e.g., Pandas, NumPy, Scikit-Learn, XGBoost). Strong experience working with cloud-based ML platforms (AWS preferred, e.g., SageMaker). Familiarity with model management and deployment tooling such ...

London-based Financial Services Clients. You will need: Extensive hands-on development experience with Python within Financial Services Strong background working with Pandas & NumPy Good experience with Django and Javascript Strong experience working within a risk environment Proficiency with Python libraries such as click apply for full job details ...