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

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