Job Overview
JOB DETAILS
Requirements
- 1-3 years of relevant work experience in projects involving large scale data analytics and machine learning.
- Proven knowledge of industry standard data analytics languages such as Python, R and SQL.
- Practical data wrangling skills (SQL, Python, R).
- Experience in data visualization using industry standard tools (Tableau, Plotly, ggplot2, RShiny and etc.).
- Experience in data science notebook technologies (Jupyter, Zeppelin, RMarkdown).
- Knowledge of data analytics stack in cloud, preferably AWS.
- Highly motivated self-starter who can provide thought leadership in data science.
- Responsive to challenging tasks.
- Ability to document and explain technical details in a concise and impactful manner.
- Strong sense of ownership and driven to manage tasks to completion.
Responsibilities
- Generate and present concise engineering and business insights to help organization make data driven decisions.
- Collaborate with subject matter experts across multiple pillars of engineering to derive requirements for analytics and metrics.
- Architect and build an end-to-end analytics platform that is scalable and reusable and will enable rapid development of analytics and metrics.
- Engage various stakeholders to locate, ingest and model siloed data sets that are essential for a comprehensive data analytics function.
- Expand the team’s analytic capabilities by building advances statistical models, including predictive models.
- Drive all aspects of the data lifecycle including data ingestion, cleanup, modeling, training, and evaluation.
- Design, develop, test, and deliver complex analytics on large data sets and unstructured log data.
Desired Qualifications
- Experience in Financial Services
- Experience in Cloud Analytics stack
- Bachelors in Computer Science, or any other Engineering Discipline or Mathematics.
- Excellent oral, written, and presentation communication skills.
Are you interested in this position?
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