1 to 25 of 161 Pandas Jobs

shared team practices Mentor peers and help grow a high-trust, high-impact engineering culture Tech Stack Python 3.x with FastAPI, Pydantic, SQLAlchemy, Pandas, and NumPy Relational databases: MySQL and PostgreSQL GCP experience is a plus, but not required Modern Middleware is a plus – e.g. Pub/Sub, Memcache Docker ...

domain regulations. Required Skills & Qualifications: Proven experience developing with Streamlit in a professional environment. Strong proficiency in Python, including data manipulation and visualization libraries (Pandas, NumPy, Plotly, etc. Experience working with banking or financial datasets. Familiarity with relational and NoSQL databases, APIs, and data integration techniques. Knowledge of banking processes ...

globally distributed team Natural curiosity and desire to grow and help shape all aspects of our team Technologies We Use and Teach Python (NumPy, Pandas, Scikit learn, PyTorch, etc.) with occasional Kotlin and Java Snowflake, GCP, AWS, and orchestration tools such as Prefect and Airflow Transformer models (BERT, LLMs, etc. ...

software engineering experience in Python, PySpark and PyAthena 3+ years of professional experience in Python as a primary language (non-scripting) Extensive experience in Pandas or NumPy Experience with ETL processes and data warehousing concepts Familiarity with cloud technologies, particularly AWS (S3, Glue, Athena, EMR) Experience using ELK Stack (Elasticsearch ...

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 ...

proficiency in Python, R, or Java. Experience with machine learning libraries such as TensorFlow, Keras, or Scikit-learn. Familiarity with data processing tools (e.g., Pandas, NumPy). Knowledge of AI model deployment and cloud services (AWS, Google Cloud, Azure). Solid understanding of algorithms and data structures. Excellent analytical skills ...

actionable insights for trading and risk management. Document system architecture, data flows, and technical processes for transparency and reproducibility. Requirements Strong proficiency in Python (pandas, NumPy, PySpark) and ETL development. Hands-on experience with AWS services (S3, Glue, Lambda) and Databricks. Solid understanding of financial market data, particularly time-series. ...

Data Engineer: Extensive hands-on experience with AWS data services Strong programming skills in Python (including libraries such as PySpark or Pandas) Solid understanding of data modelling, warehousing and architecture design within cloud environments Experience building and managing ETL/ELT workflows and data pipelines at scale Proficiency with ...

pricing, marketplace, or supply chain contexts. Experience with experimental design and statistical inference in real-world business settings. Technical Skills: Proficiency in Python (pandas, NumPy, SciPy, scikit-learn, TensorFlow/PyTorch preferred). Strong SQL skills and experience querying large-scale data platforms (e.g., Snowflake, Redshift). Familiarity with scientific ...

/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice ...

Snowflake and transform data using dbt. Serve as the subject matter expert in Python and the evolving data science stack-from core libraries like Pandas, NumPy, and Scikit-learn to advanced frameworks like XGBoost and emerging alternatives to drive continuous model innovation and optimization. Implement MLOps practices to streamline ...

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 ...

high proficiency with query languages like SQL Expert in Python or R and numerical and scientific libraries used for statistics and machine learning (e.g., Pandas, NumPy, SciPy, scikit-learn) Experience in building production level models in cloud environments (e.g., AWS, Azure) Demonstrated proficiency in time series modeling (GAMs, GLMs ...

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 ...

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 3+ 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 ...

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 ...

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 ...

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 pipelines and ML infrastructure. Proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch). Strong experience with data engineering tools (e.g., Pandas, SQL, Apache Airflow, Spark). Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Experience working with massive amounts of real ...

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 ...