1. Risk & Analytics Technology Leader
Experience
6-15 years including at least 3 years leading people
Candidate should have experience creating similar applications at a
respected global financial services company.
Responsibility
Lead design and execution of risk management, pricing, and portfolio
optimization analytics with a strong focus on developing junior team
members.
Bring data science thought leadership in predictive analytics and
machine learning.
Drive financial results for Think Liquidity by making our clients
successful, and which enables opportunity for our people.
Call: 9920698532
Email: jobs@2softsolutions.com
Web: http://www.2softsolutions.com

2. Mandatory Requirements
Must have led a team creating capital markets analytics or models for
applications such as pricing, risk management, algo trading for efficient
order execution (e.g. outperform VWAP or TWAP), model-driven or
systematic trading to derive alpha, or high frequency trading.
Evident mastery of quantitative development. Must have depth of
expertise in Java. Prefer to see experience in Scala, R, and/or Python.
Managed at least 5 people for at least 3 years.
Evidence of new invention, innovation, or achieving competitive edge
through technology.
Technology
The candidate should be equally fluent in algorithm selection and
model development as much as application development.
Strong with high performance Java. Should have exposure to another
language, such as C++, C#, Python, R, Scala, or Clojure.
Prefer exposure to Hadoop, Spark, Storm and/or other open source
NoSQL packages.
Prefer expertise with SQL Server. They should understand data
management basics such as data modelling, how to optimize query
and database performance, and guide where to use relational stores
relative other data management options.
Should have certifications earlier in their career.

3. Process
Strong agile process expertise and leadership to sustain consistent,
disciplined releases.
Prefer to see experience with CRISP-DM.
Domain expertise
Strong preference for capital markets understanding such as attributes
and behaviors of asset classes including fx, options, spread bets,
binaries, and contracts for difference. For example, an ideal candidate
will have built valuation, hedging, or alpha-generating proprietary
trading models.
Attributes
This candidate should bring a strong drive for results, and a bias for
action.
Educational background should include graduate or post-graduate
training in a quantitative subject from a competitive school. This
requirement can be waived if a candidate has a clear and sustained
record of designing, building, and operating predictive models,
complex quantitative analytics, or machine learning in production in
application(s) that are significantly material to the business results of a
global company.
Experience working in other global financial centers, such as London
or New York, is positive.