Senior Data Scientist Investment Domain
2 weeks ago
Senior Data Scientist must have 14 years Experience Onsite Boston, MA
(Subject Matter Expert) Financial/Investment / Asset Management / Fixed Income experience
Location: Boston, MA starting with 2 days working from Office and likely to get extended for all 5 days.
Job Type: Contract
Duration : 6 months subject to extension.
Interview Process: One TA team 15 minutes video call , One Internal Discussion with Trianz Technical Panel and Final Round with client All video calls.
Will be Reporting to: Delivery Manager Trianz
Please look for 14 years experience on Data Science.
Minimum 5-7 years of hands-on Financial/Investment / Asset Management / Fixed Income experience
Avoid submitting Data Analysts and worked in a project in Finance Domain. This is a Senior Role and hence people would have strong Data Science experience with Invest Domain.
Has experience in Gen AI , Language Model Strong coding experience in Python, Pyspark, Keras/tensorflow
Job Description
Role:
Data Scientist
Employment Type:
Contract
Work location:
Boston Location in USA Currently 2 days from site and likely to get extended for all days.
Work mode :
Remote
About the Role
About the Role:
We are seeking an experienced and highly skilled Data Scientist to lead the development and implementation of advanced data modeling and predictive analytics to support investment strategies.
The ideal candidate should have extensive experience in data science designing and deploying statistical modelling with at least 6 years of hands-on experience in Financial/Investment / Asset Management / Fixed Income.
Job Responsibilities
Utilize data analytics and advanced statistical techniques to inform investment decision-making and drive business growth.
Collaborate with cross-functional teams to identify opportunities for leveraging data to enhance investment strategies.
Develop and maintain a robust data infrastructure to support data-driven decision-making.
Stay updated on industry trends and best practices in data science and investments, and implement new techniques and tools as needed.
Lead the development and implementation of advanced data modeling and predictive analytics to support investment strategies.
Provide strategic guidance and recommendations to senior leadership on investment opportunities and risks based on data analysis.
Oversee the creation and maintenance of data dashboards and reports to track investment performance and identify areas for improvement.
Collaborate with other departments to ensure alignment and integration of data-driven strategies across the organization.
Mandatory Skills
Primary Skills : Has experience with data science, statistical modeling and time series analysis of financial markets data, Fixed Income Assets, Investment Banking.
Secondary Skills : Has experience in Gen AI , Language Model etc.
Required Education
Bachelor s degree in computer science or a related field.
Competencies typically acquired through an advanced degree (in Statistics, Mathematics, Data Science or other relevant field of study)
Proficiency in the mathematics underlying Machine Learning
Ability to present complex technical information in a clear and concise manner to a variety of audiences.
Required Experience
Minimum 14+ years of experience in data science designing and deploying statistical modelling with at least 6 years of hands-on experience in Financial/Investment / Asset Management / Fixed Income.
Has experience with data science, statistical modeling and time series analysis of financial markets data, Fixed Income Assets and/or Investment Banking.
Has experience in Gen AI , Language Model etc.
Worked for asset management firms in roles aligned to the front office.
Has advanced knowledge of python and/or R
Asset Allocation, Research, quat engineering
Broad experience with hands-on modelling and DS lifecycle activities, particularly in Python, and ability to communicate at a high level with DS and non-technical leaders
Knowledge of graphical packages such as plotly or gg plot
Excellent understanding of Statistical modeling, Machine Learning (Supervised, Unsupervised, Recommendation engines, Optimization etc.) Deep Learning (RNN, CNN, LSTM, Auto encoders, GANS etc.), Natural Language Processing techniques and algorithms
Strong coding experience in Python, Pyspark, Keras/tensorflow
Experience with SQL & at least one NoSQL databases
Experience of working on any of cloud platform (AWS, Azure, IBM etc.)
Work closely with data engineers to source, analyze and engineer features, collaborate with fellow data scientists to develop, test and deploy Machine Learning models
Exposure to creation of data pipelines to engineer apps deployment (CI/CD) across platforms and environments and working with ML pipelines
Demonstrate analytical and problem-solving skills, particularly those that apply to the big data environment
Travel Requirement (%)
NA
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