New York, New York
January 9th 2019
The client is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm's employees serve clients worldwide including corporations, governments and individuals from more than 1,200 offices in 43 countries. As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. The client can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture.
Work with stakeholders, identifying opportunities for leveraging data to solve for business challenges.
Identify valuable data sources / data sets that can be leveraged to improve results.
Analyze data to interpret against business opportunity and discover trends and patterns.
Process, cleanse, and verify the integrity of structured / unstructured data used for analysis.
Research and implement custom statistical models and machine learning algorithms.
Execute analytical experiments methodically to evolve an idea into successful solution.
Coordinate with engineering and software development team to integrate model into continuous business / process / software cycle.
Present information using data visualization techniques.
Communicate results and ideas to key stakeholders / decision makers.
Masters Degree in Computer Science, Statistics, Applied Math or relevant field
7+ years' practical experience as a Data Scientist with proven track record
Strong math skills (e.g. statistics, algebra, multi-variable calculus)
Expertise with R, SQL and Python; familiarity with Scala, Java or C++ is an asset
Extensive background in data mining and statistical analysis
Deep understanding of real-life applicability and limitations of machine-learning algorithms
Analytical mind and business acumen
Excellent communication and presentation skills
SKILLS & EXPERIENCE
Experience with B2B, Financial Industry, Asset Management, Sales & Marketing is highly desired.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
Expertise querying Relational / No-SQL databases and using statistical programming languages like R, Python, etc.
Experience with distributed data/computing tools: Hadoop, Hive, Spark, etc.
Experience visualizing/presenting data for stakeholders using: Business Objects, Tableau, D3.js, ggplot, etc.
Experience with data-science tools : Dataiku, Jupyter, etc.
Knowledge of open-source, 3rd party, cloud based data science / NLP / machine learning platforms (e.g. AWS or Azure offerings)
Job ID: A2260