301 to 325 of 385 Pandas Jobs

tuning paradigms, from SFT to the principles behind RLHF/RLAIF preference modelling; Strong Python skills with LangChain, HuggingFace Transformers, and data pipelines using Pandas, DVC, and Weights & Biases; Ability to define and track generation quality using BLEU, ROUGE, and editorial-specific evaluators; Experience with STT/TTS tools ...

Risk and control-oriented mindset: ability to ask incisive questions, assess materiality of model issues, and escalation issues appropriately. Proficiency in Python (NumPy, SciPy, Pandas, etc). Curious, ownership-driven, and teamwork-oriented mindset. Preferred qualifications, capabilities and skills Prior model validation or front-office quant experience in pricing, risk ...

understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.) Extensive experience with pytorch, numpy, pandas Hands‐on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.) Able to communicate technical information ...

other people depended on. Not coursework, not a notebook that ran once. Strong Python, strong Rust. Polars in particular — we don't reach for pandas here. Comfortable on AWS and on the command line. You can stand up your own infra and debug a distributed system without panicking. Solid ...

compliance/Financial Services/regulated environment preferred Highly motivated to learn about Fundment’s products Technical Expertise: Python: FastAPI, Pydantic, SQLAlchemy, PyTest, Pandas, Numpy Cloud: Experience supporting production systems Security & Compliance: Familiar with secure coding and regulated environments Values Collaborative – Deliver as a team, communicate clearly, and prioritise collective ...

within the rail , energy or mining sectors Experience in implementing low-power modes and optimising power consumption Comfort analysing device data in Python (e.g. pandas) to support engineering and product decisions Familiarity with real-time operating systems (RTOS) and their implementation Familiarity with designing, implementing and maintaining OTA firmware update ...

demonstrable impact on product and commercial outcomes. Advanced SQL — comfortable writing performant queries against large, complex datasets; window functions, CTEs, query optimisation. Strong Python — pandas, numpy, scipy, statsmodels (or equivalent); able to build analysis pipelines, not just notebooks. Solid applied statistics — experimental design, hypothesis testing, sample sizing, multiple testing correction ...

within the rail , energy or mining sectors Experience in implementing low-power modes and optimising power consumption Comfort analysing device data in Python (e.g. pandas) to support engineering and product decisions Familiarity with real-time operating systems (RTOS) and their implementation Familiarity with designing, implementing and maintaining OTA firmware update ...

Computer Science, Engineering, or a related field (or equivalent practical experience)Excellent knowledge of Python language and statistical libraries like Numpy, Pandas, PolarsDemonstrable experience in Python in a production environment Strong problem-solving skills and the ability to work in a fast-paced, collaborative and geographically distributed environmentExcellent communication ...

Risk and control-oriented mindset: ability to ask incisive questions, assess materiality of model issues, and elevate issues appropriately. Proficiency in Python (NumPy, SciPy, Pandas, etc). Curious, ownership-driven, and teamwork-oriented mindset. Preferred qualifications, capabilities and skills Prior model validation or front‐office quant experience in pricing, risk ...

understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.) Extensive experience with pytorch, numpy, pandas Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.) Able to communicate technical information ...

simulation environments from the ground up. Deep knowledge of cryptocurrency market structure, DeFi protocols and on‐chain data. Familiarity with data analysis libraries (e.g., Pandas, NumPy, SciPy) and machine learning concepts. Experience working with large‐scale time‐series data and databases (e.g., KDB+, InfluxDB, TimescaleDB). Experience in a performance ...

developing machine learning models in a cloud environmentProficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)Nice to haves: Strong knowledge of software engineering best practicesHave built applications taking advantage of Generative AI in real, production use casesFamiliarity with state of the art LLMs ...

large, complex datasets is essential. Experience with data analytics tools is highly advantageous , particularly: SQL for data querying and manipulation. Python (especially libraries like Pandas) for data analysis. Business Intelligence packages such as Looker or Power BI for visualisation and reporting. Proven Transformation Experience: Demonstrable experience contributing to finance change ...

across business functions. A passion for data‐driven decision‐making and an interest in how AI can enhance analytics workflows. Preferred Proficiency in Python (pandas) for data transformation, automation and workflow scripting. Broader experience with Google Cloud Platform (GCP), including automating data ingestion and transformation workflows. Experience working in retail ...

Data Platform StackWe employ software engineering best practices to design, test, and deploy our data platform and services using the below technologies: Python, pandas and SQL in Jupyter notebooks for analysisdbt and Databricks data platform with Delta LakeLightdash as our BI tool and semantic layerStreamlit for interactive data applicationsAirflow ...

tuning paradigms, from SFT to the principles behind RLHF/RLAIF preference modelingStrong Python skills, including working with LangChain, HuggingFace Transformers, and data pipelines (Pandas, DVC, Weights & Biases)Comfortable defining and tracking generation quality with eval metrics like BLEU, ROUGE, and building editorial-specific evaluatorsExposure to STT/TTS tools ...

Data Strategy and Analytics (DSA) for the Internal Audit function. You will design and implement production-grade data pipelines and data products, using Python (Pandas, Polars, PySpark), SQL, and modern data-lake architectures to support third-line risks. You will collaborate with audit teams and data owners to source, transform ...

hedge fund, market maker, or quantitative trading firm Proven experience building and supporting production systems for live systematic trading strategies Strong Python development (NumPy, Pandas, and the wider data ecosystem) Background as a Software Engineer/Quant Developer, not a Quant Researcher Experience with market data engineering, ML pipelines, execution ...

Python Scripting Expertise Expert-level proficiency in Python (3.x) for data engineering, with strong experience in Scripting, pandas, requests, SQLAlchemy, custom libraries, and building reusable, production-grade code. Apache Airflow Deep understanding of core concepts, including DAGs, tasks, operators, sensors, executors, hooks, and connections. Hands-on experience with Airflow architecture ...

expertise, particularly with large-scale or time-series datasets Strong programming skills in Python, Rust and/or C++ Experience with tools such as Pandas, Polars, Dask or PySpark Experience building data platforms, ETL systems, data lakes, warehouses or lakehouse architectures Knowledge of Parquet, Arrow or similar columnar formats Experience ...

some backend but mostly frontend development of the GUI and Data display for the Quant Team. Current Stack is Python and Django with R Pandas and NumpyThis innovative start-up is pioneering a new concept for the financial markets. The most important part of their product will be the enterprise ...

manipulate large, raw data sources Demonstrated proficiency in Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques Collaborative mindset with strong independent research abilities Commitment to the highest ...

exposure to bond pricing, stochastic volatility modelling and Monte Carlo simulations. Proficient in time‐series analysis, econometrics and factor‐based modelling. Advanced Python (numpy, pandas) with production deployment experience. C++ highly valued; SQL proficiency; MS Office with VBA a plus. Clear communicator able to explain complex ideas to non‐specialists. ...

commercial development experience any language Golang experience, doesn't have to be commercial PostgreSQL Celery Ideally APi DevelopmentYou will gain exposure to NumPy, SciPy, pandas, IPython and other Python libraries with ability to source, clean and manipulate large data sets as well as google mapping. You will be joining ...