Overview
QF Analytics LLC is a fintech company that develops and supports one of the world’s fastest-growing online trading platforms with a monthly trading volume in excess of $11 billion dollars. We are expanding our team aggressively and looking ideally for individuals with trading domain knowledge, who can help develop and support a robust financial trading infrastructure.
We are currently in search of a Machine Learning Engineer to join our team.
This opportunity presents an exciting chance for individuals seeking a dynamic work environment. The successful candidate will have the option to work in a hybrid capacity, commuting to offices in Miami, Chicago, Atlanta, Toronto (Canada) or Nassau (Bahamas), fostering a collaborative and engaging atmosphere. Join our team and experience the synergy that comes from working together in person, while also enjoying the flexibility and convenience of working from home a couple days a week.
Responsibilities
- Translate business requests and questions into SQL logic;
- Develop analysis templates and standards for use across the Analytics Team;
- Curate datasets from raw sources for analysis, modelling and machine learning;
- Manage a complex portfolio of data science projects, initiatives and implementations, constantly adapting to new ideas and challenges posed by Data Science/Machine Learning analysts;
- Manage data engineering platforms including the raw data layer, cleansed/aggregates layers, reporting layers and analytical layers. while integrating with other source systems;
- Work closely with Data Science team to provide environment and data automation capabilities;
- Work with DevOps team to ensure that the data architecture supports all research & strategy implementation needs;
- Work with software development & trading strategy teams to create an efficient and flexible flow of data to translate business and analytics requirements including ETL, data models, aggregations and reports for analysis;
- Convert prototypes into production data engineering solutions through disciplined software engineering practices and modern deployment pipelines;
- Work with trading strategy team to collate and organize trading system output into a structured framework to facilitate forensical analysis.
Required Qualifications
- 5+ years of experience of Database Management & Data Curation/Wrangling;
- Degree in Mathematics, Computer Science, Statistics, Economics or related fields;
- Advanced SQL/Programming Query skills, understanding of financial statistical methods, ASP .Net web apps, C#, Azure/Cloud development environments, Python, Redis, SSIS, SSAS;
- Advanced knowledge of data management, aggregation and analysis techniques;
- Strong problem-solving skills;
- Experience using statistical computer languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets;
- Experience working with and creating data architectures;
- Experience visualizing/presenting data for stakeholders using data visualization tools such as Power BI or Tableau;
- Expert knowledge of MS Excel, MS Access and VBA;
- Intermediate to advanced data manipulation ability via Excel and/or Python/SQL;
- Data pipeline and/or database development and engineering experience;
- Data visualization techniques;
Preferred Qualifications
- PhD in Mathematics, Engineering, Physics or related field;
- 4-8 years experience working in Machine Learning;
- Experience with deep learning frameworks like TensorFlow or PyTorch;
- Familiarity with C# and .NET framework;
- Familiarity with Azure Environments; specifically Azure Data Functions;
- Familiarity with Docker initialization and environment management.
What We Have To Offer
- Flexible work arrangements when in office (including working from home periodically);
- Competitive salaries, often better than industry, for comparable roles;
- Daily premium lunch catering, and keeping the office stacked with fruits and snacks;
- Arcade, foosball, snooker, pingpong, and fully equipped game room with latest generation gaming consoles on site;
- Comprehensive health benefits plan that kicks in after 90 days of successful employment, including access to exclusive employee discounts;
- Bonus and incentive programs.
