Position: Data Scientist/Quant Developer in Finance
Role: Full-time, Permanent - possible Contract-to-Hire
Timing: Immediate
Location: Boston, MA
Workplace: Hybrid
Background:
Our Boston-based client is looking for the right person to fill a specific need on the quantitative research team that builds the investment and portfolio management processes for this financial asset management firm.
***** Direct candidates only - PLEASE do not reply if you are an agency *****
Responsibilities:
- Join a rigorous, collaborative, data-driven team
- Develop ideas, signals, and forecasts
- Manage risk and generate optimal relative return
Qualifications:
- Mid-career professional, development delivery expertise
- 5+ years in the quantitative financial asset management
- 5+ years developing Python libraries for research processes
- Expertise in advanced statistics
- Experience with cloud technologies
- S3, NOSQL, columnar databases
- Hadoop/Spark/Kafka
****** Must be authorized to work in the United States *****
____________________________________________________________________________
QUESTIONS:
Are you authorized to work in the USA?
Yes/No
How many years of experience do you have in Asset/Investment Management?
How many years of experience do you have with Quantitative Investment Processes?
The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.
Responsibilities
- Analyze raw data: assessing quality, cleansing, structuring for downstream processing
- Design accurate and scalable prediction algorithms
- Collaborate with engineering team to bring analytical prototypes to production
- Generate actionable insights for business improvements
Qualifications
- Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
- At least 1 - 2 years of experience in quantitative analytics or data modeling
- Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
- Fluency in a programming language (Python, C,C++, Java, SQL)
- Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)
Salary: DOE