The Data Science team in IBM's Watson Financial Services development group is charged with design, implementation and delivery of analytic models used by a range of financial-services-oriented solutions. Our models include neural nets, clustering, natural language processing, machine learning, support vector machines, and Bayesian inference, to name just a few. We work directly with IBM Research to productize "first of a kind" prototypes and with services teams to help them help our clients to understand their business and to enable them to take action using consistent, robust, integrated analytics.
We are looking for an energetic Data Scientist or Associate Data Scientist, already familiar with statistical and machine learning models, to join our team and help reinvent financial services operations. We work largely in RegTech, with forays into FinTech on a regular basis. We provide services and software to support key value-added activities in the financial services industry as it transforms itself.
Regulation is an ever-growing challenge in financial services. Our IBM Regulatory Compliance Analytics offering reads regulations, helps to interpret them, and facilitates their integration into the firm. Would you like to help train Watson to understand regulations? Our team does that!
In an online, mobile world, traditional financial institutions are facing increasing competition from startups and disruptors in the FinTech space. We use statistical models to help banks decision more effective marketing campaigns, insurers to better understand the risks their clients face and to offer the best coverage, and to financial advisors to monitor, interact with and engage their clients more consistently. Would you like your bank to serve you better? With your contribution to our tools, it could happen!
Other exciting projects are underway. We're looking for someone who is well-grounded in statistics, familiar with data modeling (especially dimensional datamarts and big data), willing to learn and eager to participate in enhancing the financial services industry. In addition to broad and deep data and analytics skills, you'll need strong business acumen coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge.
We are a small but growing team, so it's a dynamic environment presenting new opportunities to participate, contribute and learn on a regular basis. As part of our team you'll have the opportunity to work directly with consultants, developers, marketers, financial services experts, IBM research and many others.
Position Summary and Responsibilities:
- Convert business problems into analytical solutions
- Work with experts in a business area, understand underlying business process, strategy and execution.
- Build models as needed: descriptive, predictive, prescriptive or cognitive
- Assess, document and articulate the effectiveness of predictive models
- Work with client data and augment it with self-identified sources for greater predictive power
- Identify approaches to improve the accuracy and robustness of analytics models
- Create visual and/or written presentations of analytics results and translate quantitative insights for a non-technical audience
- Deploy analytics into the business to create value.
- Work with a variety of experts in architecture, development and the financial services area.
- Refine, analyze and structure relevant data
Location: Yonge Street and Sheppard Avenue. Teams are based at strategic IBM Lab locations and presence on site is required 100% of the time.
This role will involve working with technology that is covered by embargo Export Regulations. If you are a Foreign National from any of the following embargoed countries (Cuba, Iran, North Korea, Sudan, Syria) on a work permit you are not eligible for employment in this position.
Required Education: Master's Degree
Preferred Education: Doctorate Degree
Required Technical and Professional Expertise:
- Master's Degree in a quantitative discipline
- Experience in one of the following fields: mathematics, statistics, operations research, engineering, economics or quantitative finance.
- Exposure to course work or projects in Natural Language Processing (NLP)
- Programming or scripting skills for data science (e.g., R, python, Scala, SPSS, SAS, Matlab)
- English: Fluent
Preferred Technical and Professional Experience:
- PhD in Mathematics or Statistics
- At least 1 year's experience in identifying and defining requirements and turning functional requirements into a predictive or prescriptive analytics solution that addresses difficult business problems.
- Exposure to working with financial data (e.g., stock market, retail banking, asset management or insurance premia).
- Demonstrated knowledge of relational, nosql and dimensional data modeling
Must be eligible/legally entitled to work in Canada
IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.