Senior Data Scientist
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Overview
We are seeking an experienced and innovative Senior Data Scientist to join our dynamic team. The ideal candidate will possess a strong background in statistical analysis and machine learning in Financial industry, with the ability to apply these skills to solve complex business problems. As a Senior Data Scientist, you will lead data-driven projects, innovation on Data science and Machine learning capability build and collaborate with cross- functional teams to enhance our data capabilities.
We are seeking an experienced and innovative Senior Data Scientist to join our dynamic team. The ideal candidate will possess a strong background in statistical analysis and machine learning in Financial industry, with the ability to apply these skills to solve complex business problems. As a Senior Data Scientist, you will lead data-driven projects, innovation on Data science and Machine learning capability build and collaborate with cross- functional teams to enhance our data capabilities.
Key Responsibilities Data Analysis: Conduct advanced statistical analysis to interpret and extract meaningful
insights from large datasets. Extract data into presentable reports, charts, and graphs.
Analyze and interpret data to find outliers, understand root cause, business impact,
correlations/discrepancies, and propose changes/alternate solutions. Discover
patterns/root causes, and generate insights to drive product enhancements
Machine Learning: Develop, implement, and optimize machine learning models to
support various business initiatives. Analyze and evaluate the quality of data used for
model training and testing. Create and present proposals and results in an intuitive,
data-backed manner, along with actionable insights and recommendations to drive
business decisions
Project Leadership: Lead data science projects from conception to deployment, ensuring
timely delivery and high-quality outcomes.
Collaboration: Work closely with product managers, engineers, and other stakeholders
to understand business needs and align data solutions accordingly.
Mentorship: Mentor and guide junior data scientists and analysts, fostering a
collaborative and growth-oriented environment.
Data Infrastructure: Contribute to the development and maintenance of data pipelines,
ensuring data accuracy and accessibility.
Reporting: Prepare and present analytical reports and visualizations to communicate
findings to both technical and non-technical audiences.
insights from large datasets. Extract data into presentable reports, charts, and graphs.
Analyze and interpret data to find outliers, understand root cause, business impact,
correlations/discrepancies, and propose changes/alternate solutions. Discover
patterns/root causes, and generate insights to drive product enhancements
Machine Learning: Develop, implement, and optimize machine learning models to
support various business initiatives. Analyze and evaluate the quality of data used for
model training and testing. Create and present proposals and results in an intuitive,
data-backed manner, along with actionable insights and recommendations to drive
business decisions
Project Leadership: Lead data science projects from conception to deployment, ensuring
timely delivery and high-quality outcomes.
Collaboration: Work closely with product managers, engineers, and other stakeholders
to understand business needs and align data solutions accordingly.
Mentorship: Mentor and guide junior data scientists and analysts, fostering a
collaborative and growth-oriented environment.
Data Infrastructure: Contribute to the development and maintenance of data pipelines,
ensuring data accuracy and accessibility.
Reporting: Prepare and present analytical reports and visualizations to communicate
findings to both technical and non-technical audiences.
Qualifications
- Education: Masters or Ph.D. degree in Data Science, Computer Science, Statistics, or a related field.
- Experience: Minimum of 5 years of experience in data science or a related field.
- Expert in AWS AI/ML, GenAI tools e.g. SageMaker, Bedrock etc.
- Technical Skills: Proficiency in programming languages such as Python, R, and SQL.
- Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn) and data visualization tools (e.g., Tableau, Power BI).
- Experienced in Identity and Access management, data protection, data privacy standards
- Experienced in building model/tooling around continuous auditing
- Analytical Skills: Strong analytical and problem-solving skills, with a keen attention to detail.
- Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex concepts to diverse audiences.
- Team Player: Ability to work effectively in a team environment and independently.
Preferred Qualifications
- Experience in the industry relevant to the companys domain (e.g., finance, healthcare, e-commerce).
- Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure).
- Experience with big data technologies (e.g., Hadoop, Spark).
- Published research or contributions to open-source projects.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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