Senior Data Scientist
6 months ago
Collaborate with product design and engineering to develop an understanding of needs.
- Research and advise innovative statistical models for data analysis.
- Communicate findings to business stakeholders. Enable smarter business processes—and implement analytics for actionable insights.
- Keep current with technology and industry developments.
- Use various statistical techniques and algorithms to extract knowledge and insights from structured and unstructured data. Translate model output into meaningful business insight.
- Responsibilities:
- Establish and mentor junior Data Scientists.
- Performing people management responsibility.
- Responsible for technology and platform vision.
- Work closely with “Data Products’ Owners” to set up use-cases priorities, Budget, and backlog.
- Work closely with Technology teams to design, build, test, deploy, maintain, and improve technology solutions and models.
- Collects and determines data from appropriate sources to assist in determining business needs and requirements.
- Interacts with both Data Engineers and business owners to satisfy the use-case requirements
- Follows and embraces best practices when it comes to methodologies, standards, and processes.
- Spread Design Thinking and Agile methodologies
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies.
- Assess the effectiveness and accuracy of new data sources and data-gathering techniques.
- Build tunes and deploy predictive statistical models for extracting business insights.
- Exploit ML for developing business use cases
- Provides thought leadership by researching best practices, conducting experiments, and collaborating with business leaders.
**Requirements**:
- Bachelor's degree in Economics, Computer Science, Engineering, Statistics, Mathematics, Physics, Operations Research, or related discipline with an excellent academic record.
- Solid understanding of foundational statistics concepts and ML algorithms: linear/logistic regression, random forest, boosting, GBM, NNs, etc.
- Experiences in building data science solutions with real business problems. (e.g. recommendation building, customer journey, customer experience enhancement, etc).
- Fluency in at least one of the following languages: Python, Java, Scala, R.
- Ability to access, manage, transfer, integrate, and analyze complex datasets, especially using SQL and No-SQL.
- Experience with sci-kit-learn and pandas (or equivalent tools).
- Master's or Ph.D. degree (preferred) in computer science, statistics, neuroscience, engineering, mathematics, or physics.
- preferred but not must an experience with working on large data sets, especially with Hadoop and Spark.
- strong communication skills with the ability to align the organization on complex technical decisions.
- active coach and mentor whose goals are to grow and maximize the team's potential.
- High energy and passionate individual who inspires teammates to reach their maximum potential
- Excited about trying new solutions outside standard approval.
- Embraces a culture of trust, free thought complete transparency.
- Brave and rebellious, willing to challenge the status quo.
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