Data Science Leader
hace 2 días
Tiger Analytics is a pioneer in harnessing the power of AI and analytics to tackle complex organizational challenges globally.
We develop tailored solutions powered by data and technology for leading Fortune 100 companies, with a presence in multiple US, UK, Indian, and Singaporean cities, and a substantial remote global workforce.
As a market leader in AI and analytics consulting in the retail & CPG industry, we generate over 40% of our revenue from this sector, which is our fastest-growing area.
We are seeking a seasoned Principal Data Scientist with a strong blend of data analytics expertise, solid knowledge of Data Science Models, and strong coding capabilities to join our team.
Key Responsibilities:- Apply the latest data science techniques to solve business problems in the Retail and CPG space.
- Effectively communicate the analytics approach and its alignment with business objectives to stakeholders.
- Develop clear, actionable solutions and recommendations for clients' business needs.
- Undertake hands-on work on data analytics, model development, and testing, and prepare data files for visualization platforms.
- Conduct business analysis on data and provide insights.
- Coordinate with decision-makers to translate business questions into verifiable hypotheses and data models.
- Work across various analytics problems and provide thought leadership.
- Interact with onsite teams and clients to gather requirements and provide updates.
- Stay connected with external sources of ideas through conferences and community engagements.
Support demands from regulators, investor relations, etc., to develop innovative solutions using cutting-edge techniques and tools.
Requirements:- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
- Minimum of 8 years of experience in Data Science and Machine Learning.
- Solid understanding of machine learning algorithms and statistical analysis.
- 5+ years of Model building and Enterprise-level deployment experience.
- Proficiency in Python and PySpark programming languages commonly used in Data Science.
- Real-time Series for FE and Real-time Process Execution/Scoring.
- Creation of Docker Containers to execute code in Kubernetes Environment.
- Proficiency using Azure Databricks.
- Experience with cloud platforms such as Azure and AWS is a plus.
- Ability to preprocess and clean large datasets for analysis.
- Strong problem-solving skills and ability to think analytically.
- Excellent communication and presentation skills.
- Ability to work effectively in cross-functional teams and manage multiple projects simultaneously.
- Experience in Manufacturing space is a bonus.
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