Tiger Analytics Hiring Drive 2024: Tiger Analytics Hiring Drive 2024 for its Data Scientist. Tiger Analytics Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a Degree in Computer Science, Data Science, Mathematics, or a similar field. if you are interested, please apply as soon as possible.
Company Name: Tiger Analytics
Role: Data Scientist
Location: Across India
Experience: 2 – 5 yrs
Qualification: Degree in Computer Science, Data Science, Mathematics, or a similar field
Batch: Any
Job Type: Full Time
Salary: ₹2L – ₹10 LPA
Tiger Analytics Hiring Drive 2024
Job Description:
- We are looking for a Lead Data Scientist to lead a technical team and help us gain
- useful insight out of raw data.
- Lead Data Scientist responsibilities include managing the data science team, planning
- projects and building analytics models.
- You should have a strong problem-solving ability and a knack for statistical analysis.
- If you’re also able to align our data products with our business goals, we’d like to meet you.
- Your ultimate goal will be to help improve our products and business decisions by making the most out of our data.
Requirements:
- Proven experience as a Data Scientist or similar role
- Solid understanding of machine learning
- Knowledge of data management and visualization techniques
- A knack for statistical analysis and predictive modeling
- Good knowledge of R, Python and MATLAB
- Experience with SQL and NoSQL databases
- Strong organizational and leadership skills
- Excellent communication skills
- A business mindset
- Degree in Computer Science, Data Science, Mathematics, or a similar field
- Familiar with emerging/cutting edge, open source, data science/machine learning
- libraries/big data platforms
Responsibility:
- Conceive, plan and prioritize data projects
- Ensure data quality and integrity
- Interpret and analyze data problems
- Build analytic systems and predictive models
- Align data projects with organizational goals
- Lead data mining and collection procedures
- Test performance of data-driven products
- Visualize data and create reports
- Build and manage a team of data scientists and data engineers
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