美国最新DATA岗位职位来袭
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1
Data Science intern |
Job Type: Internship Location: Chicago, IL |
Responsibilities • Execute analytical work such as segmentation, forecasting, simulation and mathematical programming, • Conduct an effective and efficient proof of concept and proof of value project, and • Define reliable, controlled, automated analytic processes. • Document and present results Qualifications • This position requires a graduate student in a quantitative science, such as (but not limited to) analytics, mathematics, statistics, econometrics, operations research or computer science, and a genuine interest in the business impact of the application of advanced analytics. • The position greatly benefits from hands-on experience with analytic tools such as Python, SAS, Matlab, or R. |
2
Data Engineer Intern |
Job Type: Internship Location: Newark, NJNewark, NJ |
Responsibilities • Assist the business intelligence team in day to day activities and projects. One of the primary projects is to assist with the data management process to collect, clean, transform and store data from relevant data sources into our data storage and analytic environment. • Additionally, the intern may assist with data engineer and project manager to review and optimize machine learning models. • Additional tasks may include the exploration and experimentation of new workflows and technology solutions to enhance our analytic activities. Qualifications • Savvy with data analysis and software technology including strong Excel skill. • Basic modern BI skill (PowerBI, Tableau, Qlik, etc), MS Access and SQL database knowledge are preferred. • Data science and data engineering skills are highly preferred. • Good business acumen to understand the business user roles and needs. Fast learner to develop general awareness of products and markets. • Clear communication skill is required to work with stakeholders and various departments. • Active degree in analytics or computer science is required. |
3
Data Science Analyst |
Job Type: Full-time Location: Boston, MA |
Responsibilities • Collaborate with data sourcing and commercial management, compliance, data science engineers, research, portfolio management, operations and technology to understand investment needs and manage the on-boarding process of new diverse data sets for Man. • Perform thorough data vendor comparison analysis covering data integrity, coverage and aggregation methodologies. • Analysis and evaluation of datasets to assist investment teams with finding alpha signals • Develop large-scale data analytic capabilities to extract insights from structured and unstructured data. • Build automated processes for reviewing and analysing diverse sets of information • Support the analytical needs of investment teams inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. • Contribute towards building a robust data pipeline; including performing data analytics, building data dashboards and implementing an optimised on-going data management process. • Curate and present relevant research and technical documentation to build and maintain an updated, accurate and accessible knowledge store. • Ensure that vendors are actively engaged with Man’s requirements and provide a continuous feedback loop between Man’s investment units and vendors. • Contribute to initiatives across the Man Data Science group to expand and improve the firm’s data ecosystem. • Conduct industry research to identify new initiatives in financial markets, market data and alternative data. Qualifications • Strong academic record and higher education degree with high mathematical and computing content e.g. computer science, mathematics, physics, statistics or another disciplines involving technical and quantitative analysis techniques. • Proven experience and fluency with data analysis techniques in SQL and an object oriented language, preferably Python, along with relevant libraries e.g. NumPy/SciPy/Pandas. • At least 1 year of experience as a Data Scientist, quantitative researcher or in a similar role • Previous experience with reporting and visualisation, preferably using python, and creating technical solutions for operation and data related tasks/processes. • Working knowledge of Mongo DB, Linux / UNIX, Git, Jira is preferable. • Demonstrate evidence of strong analytical and communication skills, both written and oral. • Financial industry experience preferred. • Excellent attention to detail. • Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities. |
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