Software Engineer with up to 6+ years of hands-on Python experience. Familiarity with AWS Serverless and related technologies would be advantageous. Strengths in Pandas, Polars, Pytest, Postgres, and CI/CD is essential. If you're interested in Agile methodologies, and have a curiosity about DDD and Event-Driven more »
quality, performance, and scalability. Qualifications Bachelor’s Degree in Computer Science, Information Systems, Mathematics, etc. 7+ years in Python and libraries like PyTorch, NumPy, Pandas, Matplotlib, QuantLib, etc Experience in Systems that handle high-throughput, low-latency data Experience with multi-threading, concurrency, and high-frequency trading (HFT). Experience more »
including data integration, modelling, optimisation and data quality Exceptional understanding of Python Experience developing in the cloud (AWS preferred) Solid understanding of libraries like Pandas and NumPy Experience in data warehousing tools like Snowflake, Pyspark, Databricks Commercial experience with performant database programming in SQL Capability to solve complex technical issues more »
Have a Bachelor's or Master's degree in Computer Science or related field. 3+ years of data engineering experience with strong Python (including Pandas) skills. Strong proficiency in Object-Oriented Programming. Have strong problem-solving and communication skills. Experience working in Commodities, Trading or Financial Services markets. For more more »
for improvement. Qualifications Maths/Computer Science/Engineering Masters or PhD from a top-ranked institution Experience with common Python libraries: NumPy, SciPy, Pandas, SQLite etc A firm grasp of advanced undergraduate maths degree topics, in particular - Linear Algebra, Complex numbers, Optimisation theory, Machine learning Experience or demonstrable interest more »
microstructure experience would be very beneficial. Proficiency in programming languages such as C++, Python or MATLAB along with experience in data analysis libraries (e.g., pandas, NumPy) and version control systems (e.g., Git). Familiarity with low-latency trading systems, high-performance computing, and algorithmic trading strategies. Strong academic background in more »
demonstrated by a history of identifying and implementing automation opportunities. Experience working with a variety of data storage and manipulation tools such as SQL, Pandas, Elasticsearch & Kibana, Snowflake. Ability to recognize patterns and establish standards to streamline development and enhance reliability. Excellent interpersonal skills, enabling positive and collaborative relationships with more »
as a Data Scientist, with a strong focus on machine learning and time series forecasting. Expertise in Python and its data science libraries (e.g., Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch). Solid understanding of ML and data pipeline architectures and best practices. Experience with big data technologies and distributed computing more »
a tech team using a diverse tech stack including: Backend: Python, FastAPI, PostgreSQL, Vespa, SQLAlchemy, Flask. Frontend: React, Next.js. Data Science: Python, Jupyter, PyTorch, Pandas, Spacy, Huggingface, Numpy, Streamlit, Weights and biases. Infra: Pulumi, Docker, AWS AppRunner, Step Functions, Grafana cloud monitoring, Prefect. Who you are Must haves: Experience using more »
for improvement to implement practical solutions. Key Requirements Background in Python Development from an engineering or development environment Experience with Airflow, Cloud (AWS) and Pandasmore »
implementation of systematic strategies in production, build tools to monitor strategies, build research infrastructure - with a heavy focus on data engineering. Tech stack: Python, Pandas, AWS, Kafka Requirements: Bachelors or Masters in an engineering or quantitative subject Strong Python production coding skills (deployed to AWS) Strong data engineering skills (e.g. more »
haves: Looking for a junior Python developer with a few years of professional experience. Proficiency in Python Ideally in data science libraries like NumPy, Pandas etc. Application building experience (multi-processing, API dev etc.) – not just data analysis Competency in SQL Some (but any) cloud experience Strong communication skills, teamwork more »
Utilize existing and new datasets to develop significant insights and decision support tools for investment teams. Required Skills: Advanced knowledge and experience with Python (Pandas, NumPy + more) and SQL Strong background in advanced analytics and statistical modelling Strong analytical and quantitative skills Experience working with large, unstructured data sets more »
Quant Finance Strong Python expertise is required, and C++ expertise is a plus. Quantitative background (eg: statistics, linear algebra, or calculus) and/or Pandas and Numpy expertise that allows close collaboration with researchers a strong plus Experience with data driven python pipelines, data/ML platform design production model more »
Python Experience using front-office pricing libraries Comfortable with relational and timeseries databases Exposure to distributed systems and messaging (e.g. Kafka) Comfortable with Numpy, Pandas and Jupyter Highly self-motivated, willing to take initiative and make technical decisions more »
in using quantitative methods for strategy parameter optimization Prior experience at a top tier hedge fund, proprietary trading house or investment bank Exposure to pandas, numpy, scikit-learn, statsmodels-tsa, TensorFlow, Keras, and Matplotlib libraries more »
bonds) and modern OIS/Libor techniques. Preferred experience in US Treasury and European government bond markets. Proficient in Python and data manipulation libraries (Pandas, NumPy, SciPy). Experience with Dash/Plotly or similar visualization software. Skilled in database programming (kdb, SQL) and MS Excel with real-time data. more »
GCP.Data Models: Ability to create and implement both logical and physical data models.Mapping Specifications: Competence in creating detailed mapping specifications.Python: Knowledge of Python, particularly Pandas, for data analysis.Looker Core/LookML: Experience with Looker Core or LookML (not Looker Studio).User Acceptance Testing (UAT): Proficiency in planning and executing UAT.Data more »
Ability to create and implement both logical and physical data models. Mapping Specifications : Competence in creating detailed mapping specifications. Python : Knowledge of Python, particularly Pandas, for data analysis. Looker Core/LookML : Experience with Looker Core or LookML (not Looker Studio). User Acceptance Testing (UAT) : Proficiency in planning and more »
field. • 5+ years of experience as a Data Engineer or in a similar role. • Strong proficiency in Python and experience with relevant libraries (e.g., pandas, numpy). • Extensive experience with ETL tools and processes. • Familiarity with data warehousing concepts and technologies (e.g., Redshift, BigQuery, Snowflake). • Proficient in SQL and more »
field. 8+ years of experience as a Data Engineer or in a similar role. Strong proficiency in Python and experience with relevant libraries (e.g., pandas, numpy). Extensive experience with ETL tools and processes. Familiarity with data warehousing concepts and technologies (e.g., Redshift, BigQuery, Snowflake). Proficient in SQL and more »
or more relevant database technologies e.g. Oracle, MongoDB Proficient with a range of open source frameworks and development tools e.g. NumPy/SciPy/Pandas, Pyramid, AngularJS, React Familiarity with a variety of programming styles (e.g. OO, functional) and in-depth knowledge of design patterns Personal Attributes: Candidates must have more »
trading dynamics, and market microstructure. Proficiency in programming languages such as Python, R, or C++, with experience in quantitative libraries and tools (e.g., NumPy, pandas, TensorFlow). Experience with data analysis, statistical modeling, and machine learning techniques applied to financial data. Knowledge of trading platforms, order execution systems, and electronic more »
and productionalize containerized algos for deployment in hybrid cloud environments (GCP, Azure) Connect and blend data from various data sources within enterprise tools (python, pandas, or SQL) to enable application of Data Science methods Create metrics and analytical reports to ensure data quality and business value. Clean, structure and normalize more »
Influencer Marketing Awards 2022: “Industry Choice of SaaS or Technology” and “Best Influencer Marketing Technology” OUR DATA STACK: Our main technologies are: Python (ScikitLearn, Pandas, Numpy, Scipy) PostgreSQL Google Cloud KEY REMIT: Your responsibilities will fall across two areas: Creating algorithms and using existing technology to generate reports and insight more »
