46 to 70 of 105 Pandas Jobs

expertise in MLOps implementation for deploying, monitoring, and managing ML models in production environments. Proficiency in Python and experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy Strong understanding of cloud technologies and AI/ML platforms, particularly AWS SageMaker. Solid grasp of software engineering principles including design patterns, testing, CI/CD, security, and version More ❯

Must Have 5+ years professional Python development experience. Extremely effective in writing clean, modern Python code. Experience building and documenting high-quality APIs for developers. Deep Python ecosystem expertise: Pandas, Numpy, Bokeh, PyArrow, matplotlib, IPyWidgets, Jupyter, uv, etc. Proven experience building large data pipelines/ETL workflows. Comfortable working in Jupyter notebooks. An understanding of crypto or TradFi markets and More ❯

master’s degree in a STEM subject (Mathematics, Computer Science or Engineering) Experience working in a data science or consulting role In-depth experience of working with Python and Pandas An entrepreneurial spirit and drive to work in an early stage start-up A curious mindset to understand how we can improve things and better help our clients address commercial More ❯

always work with our data, so you will need to understand how to develop your own models Strong programming skills and experience working with Python, scikit-learn, SciPy, NumPy, Pandas and Jupyter Previous experience in finance is not required, although an interest in finance and the motivation to rapidly learn more is a prerequisite for working here. Why should you More ❯

automation-ready using methodologies. Python Development - Strong proficiency in Python programming including object-oriented design, asynchronous programming, error handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep More ❯

to leverage AI tooling to get bootstrapped quickly is a must. Core AI & Machine Learning Python Vertex AI/Hugging Face LangChain/BAML — LLM frameworks Langfuse, LangSmith — Observability Pandas, NumPy, scikit-learn, PyTorch — Data & ML stack Data & Infrastructure BigQuery — Cloud data warehouse PostgreSQL — Application data Pulumi — Infrastructure as Code (TypeScript) Google Cloud Platform (GCP) — Cloud provider GitHub Actions — CI More ❯

have Must be strong in Python Java and/or REXX is helpful but not a must have Data manipulation experience is a big plus - Numpy/PySpark/Pandas are a big plus IAC tools like Terraform and/or CloudFormation would be very beneficial More ❯

cloud-based solutions. Experience with Cloud services such as Azure Data Services, ADLS and AKS. Experience with Python and PySpark for distributed data processing, along with proficiency in Numpy, Pandas and other data manipulation libraries. Experience in optimizing big data architectures for high availability and performance. Strong problem-solving skills, analytical mindset, and ability to work in fast-paced environments.Experience More ❯

proofs-of-concept , model monitoring , and adoption of emerging AI tech. What We’re Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving skills. Passion for innovation More ❯

or similar role focused on Python coding. It is essential to have good knowledge of Python built in data types/functionality as well as associated tools such as Pandas/Polars, and web frameworks. The ideal candidate will be passionate about the latest AI/Machine Learning/Automation techniques and tools, with some exposure to web scraping tools More ❯

or similar role focused on Python coding. It is essential to have good knowledge of Python built in data types/functionality as well as associated tools such as Pandas/Polars, and web frameworks. The ideal candidate will be passionate about the latest AI/Machine Learning/Automation techniques and tools, with some exposure to web scraping tools More ❯

large, complex datasets. Desirable Experience & Skills Practical knowledge of data engineering practices (designing and building robust data pipelines) Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel More ❯

Stay informed on emerging trends, technologies, and best practices in data science. Experience Required: Proven experience as a Data Scientist with proficiency in Python and libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, and Plotly. Strong background in statistical modelling, machine learning, and data mining, with experience working on time-series data. Knowledge of data engineering principles, including pipelines, databases More ❯

users Present findings and recommendations to non-technical stakeholders 3. Ideal Qualifications 5+ years of applied data science or analytics experience in business settings Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills Experience with data visualization tools (e.g., Tableau, Power BI) Solid understanding of statistical modeling, experimentation, and A/B testing Strong communication skills for More ❯

improve infrastructure, code, and surrounding processes. Ability to write high-quality code in Python 3 and C++. General understanding of ML and experience working with basic models. Proficiency with pandas/pyspark or similar libraries for data analysis. Benefits A dynamic and international environment within a fast-growing tech company. Competitive salary at the upper end of the market, along More ❯

improve infrastructure, code, and surrounding processes Ability to write high quality code in Python 3 and C++ General understanding of ML and experience working with basic models Proficiency with pandas, pyspark or similar libraries for data analysis Benefits A dynamic and international environment within a fast growing tech company Competitive salary at the upper end of the market, along with More ❯

or related pricing/trading systems Solid understanding of algorithms, data structures, and design patterns Experience with relational and NoSQL databases (PostgreSQL, Redis, MongoDB) Proficiency in data processing using pandas, NumPy , and working with APIs Understanding of CI/CD pipelines and DevOps practices Preferred: Quantitative analysis, financial modeling, or experience with trading systems Familiarity with distributed systems and event More ❯

or related pricing/trading systems Solid understanding of algorithms, data structures, and design patterns Experience with relational and NoSQL databases (PostgreSQL, Redis, MongoDB) Proficiency in data processing using pandas, NumPy , and working with APIs Understanding of CI/CD pipelines and DevOps practices Preferred: Quantitative analysis, financial modeling, or experience with trading systems Familiarity with distributed systems and event More ❯

key strategic initiatives, including price, volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another product-heavy industry. Strong knowledge More ❯

innovation and data transformation initiatives Knowledge & Experience Required Essential Skills & Experience: 5+ years in analytics, data engineering, BI, or data management roles Advanced skills in SQL and Python (especially Pandas, NumPy) Proficiency in Tableau, Power BI, Excel, or similar tools Experience with cloud platforms (e.g., Snowflake, Databricks) and ETL workflows Ability to translate business needs into technical data solutions Meticulous More ❯

kinetics. Interest in simulation, modeling workflows, and their application in real-world pharma/biotech contexts. Basic to intermediate Python programming skills, especially with scientific libraries (e.g., NumPy, SciPy, pandas). Nice to Have Experience with Pyomo or CasADi. Familiarity with bioprocesses or pharma case studies. Curiosity about AI, workflow automation, or cloud-based platforms. Soft Skills Proactive, reliable, and More ❯

if you: Have over 3+ years of professional experience in data science or applied analytics. Are highly skilled in Python and Jupyter notebooks. Have experience using libraries including numpy, pandas, scipy, sympy, scikit-learn, torch, tensorflow. Have a bachelor's degree in data science, statistics, computer science, or related field in the U.S., Canada, New Zealand, UK or Australia. Have More ❯

experience in ML Engineering or a related field (we value diverse backgrounds!) Strong foundation in software engineering principles and best practices Proficiency in Python and data science libraries (e.g., pandas, scikit-learn, PyTorch) Familiarity with version control systems and CI/CD principles Understanding of statistical models and their evaluation methodologies We encourage applications from candidates of all backgrounds. If More ❯

degree in a quantitative field (e.g. Statistics, Mathematics, Physics, Machine Learning) You're confident in Python (production-level) and SQL, and at home with modern ML libraries such as Pandas, scikit-learn, and TensorFlow You have practical experience with MLOps frameworks and deploying models You're skilled at bringing data to life through visualisation, and tools like Tableau feel natural More ❯

GIS, ArcGIS), remote sensing techniques, and the application of data science in the IC. Expert proficiency in Python (or similar languages) and experience with data science libraries (TensorFlow, PyTorch, Pandas, NumPy). Strong experience with big data processing tools (e.g., Spark, Hadoop, AWS or Azure cloud platforms). Expertise in working with geospatial data formats (e.g., GeoTIFF, Shapefiles, WMS, WFS More ❯