system design, application development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming and database querying. Overall knowledge More ❯
LangChain, TensorFlow, and PyTorch. Exposure to LLMs from model families such as Anthropic, Meta, Amazon, and OpenAI. Familiarity with tools and packages like Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks. Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Proficiency in data pre-processing, data More ❯
influence everything we do. Preferred Qualifications Familiarity building scalable services in a microservices architecture. Familiarity with statistical tools such as SAS, or Python (with NumPy, SciPy, Pandas) Familiarity with public cloud platforms, such as AWS, Azure, or GCP. Strong testing automation experience, preferably in unit frameworks Diverse and Inclusive At More ❯
accurate insights. Experience: Hands-on development of LLM-based applications (OpenAI, Anthropic, Hugging Face, etc.). Strong Python programming skills, including libraries like pandas , numpy , and experience with data pipelines. Familiarity with frameworks such as LangChain , Semantic Kernel , or similar. Prior experience working with AI evaluation techniques and agent orchestration More ❯
Looking For: Previous experience at a tier-one bank or large financial organisation is a plus. Extensive proficiency in Python, including libraries such as numpy and scipy. Experience in Market Risk/Trader Risk development is highly advantageous, though not mandatory. Strong knowledge of Rates and Fixed Income products is More ❯
Looking For: Previous experience at a tier-one bank or large financial organisation is a plus. Extensive proficiency in Python, including libraries such as numpy and scipy. Experience in Market Risk/Trader Risk development is highly advantageous, though not mandatory. Strong knowledge of Rates and Fixed Income products is More ❯
Looking For: Previous experience at a tier-one bank or large financial organisation is a plus. Extensive proficiency in Python, including libraries such as numpy and scipy. Experience in Market Risk/Trader Risk development is highly advantageous, though not mandatory. Strong knowledge of Rates and Fixed Income products is More ❯
understanding of mathematics and statistics. Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch. Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Familiarity with big data technologies (e.g., Hadoop, Spark). Excellent problem-solving skills and attention to detail. Ability to work independently and as More ❯
experience. Experience in system design, application development, testing, and operational stability, especially with data pipelines. Proficiency in Python and data manipulation libraries such as NUMPY and PANDAS. Experience with PySpark, including analysis, pipeline building, tuning, and feature engineering. Knowledge of SQL and NoSQL databases, including joins, aggregations, and tuning. Experience More ❯
years of experience in a quantitative, analytics, or developer role within a financial institution or trading environment. Strong proficiency in Python (e.g., Pandas, NumPy, Jupyter) and experience building data pipelines , analytical tools , or dashboards . SQL experience is a plus. Proficiency in Excel and data visualization platforms such as Power More ❯
years of experience in a quantitative, analytics, or developer role within a financial institution or trading environment. Strong proficiency in Python (e.g., Pandas, NumPy, Jupyter) and experience building data pipelines , analytical tools , or dashboards . SQL experience is a plus. Proficiency in Excel and data visualization platforms such as Power More ❯
to apply this process when handling structured or unstructured data Confident with using common data science tooling such as Jupyter notebooks, pandas, matplotlib, seaborn, numpy API testing and security tools: Postman, Burp Suite, OWASP ZAP, etc. Strong knowledge of database management systems (DBMS) such as MySQL Hands-on experience with More ❯
to apply this process when handling structured or unstructured data Confident with using common data science tooling such as Jupyter notebooks, pandas, matplotlib, seaborn, numpy API testing and security tools: Postman, Burp Suite, OWASP ZAP, etc. Strong knowledge of database management systems (DBMS) such as MySQL Hands-on experience with More ❯
datasets using Python. Practical expertise and work experience with ML projects, both supervised and unsupervised. Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy More ❯
Limited Technical Recruitment Consultant at SmartChoice International for UK & Europe Job Description: Proficient in coding and software design, with expertise in Python frameworks like NumPy, Pandas, Django, or Flask. Experience in developing secure, high-quality code, troubleshooting technical issues, and creating architecture artifacts for complex applications. Good experience in system More ❯
data quality initiatives, and automation projects. What You’ll Need Strong experience in Python, SQL, and common data science libraries (e.g. pandas, scikit-learn, NumPy). Experience in developing, testing, and deploying data models in a real-world business setting. Comfortable working with unstructured data and navigating ambiguity in fast More ❯
and machine learning - Experience with prompting techniques for LLMs PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - PhD in math/statistics/engineering or other equivalent quantitative discipline More ❯
Experience with neural deep learning methods and machine learning PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. - Master's degree in math/statistics/engineering or other equivalent More ❯
datasets using Python. Practical expertise and work experience with ML projects, both supervised and unsupervised. Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy More ❯
datasets using Python. Practical expertise and work experience with ML projects, both supervised and unsupervised. Proficient programming skills with Python, including libraries such as NumPy, pandas, and scikit-learn, as well as R. Understanding and usage of the OpenAI API. NLP: tokenization, embeddings, sentiment analysis, basic transformers for text-heavy More ❯
analytical techniques, including sampling, regression, distribution properties, and weighting Proper use of statistical tests in real-world applications Proficiency in Python libraries such as NumPy, SciPy, Pandas, scikit-learn, and others Working knowledge of SQL, data structures, and databases (Snowflake is desirable) This organization is pragmatic and humble, seeking like More ❯
regression, properties of distributions, weighting sample-based data, and proper use of statistical tests in real-world applications. Proficiency with Python libraries such as NumPy, SciPy, Pandas, scikit-learn, and others related to data and machine learning. Working knowledge of SQL, data structures, and databases (Snowflake is desirable). This More ❯
of distributions, weighting sample-based data, and proper usage of statistical tests Real-world applications of these techniques Proficiency in Python libraries such as NumPy, SciPy, Pandas, scikit-learn, and others related to data and machine learning Working knowledge of SQL, data structures, and databases (Snowflake is desirable) This organization More ❯
statistical and analytical techniques and concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This More ❯
statistical and analytical techniques and concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This More ❯
