- To advance the organization by developing algorithms to build models that uncover connections and make better decisions without human intervention.
- The role is an inter-disciplinary field that uses scientific methods to extract structured and unstructured data, converting it to insights.
- Algorithms, Data Bases and Programming languages are the main ingredients of this role.
- Develop models and train them,
- Research on new technologies,
- Participate in recruitment process.
- Leverage various data science methods such as machine learning, statistical modeling, forecasting, and causal inference to understand user behavior and predict growth of different customer segments,
- Research, develop and deploy algorithms to extract meaning and interpretation from data,
- Implementation of data projects end-to-end from extracting data to interpretation,
- Enhance performance of business with proposing idea with supporting insights,
- Create solutions to ease business daily operation and increase profit.
- Master's degree in Computer science, mathematics, and statistics, Master's is a plus,
- Expertise with structured and unstructured data,
- Expertise with methods in Machine learning and statistics,
- Strong knowledge of SQL and NoSQL,
- Fluency in Python, R or similar scripting language,
- Experience in distributed data processing systems(Hive, Redshift, Presto, Snowflake, etc),
- Experienced in Data warehousing, cleaning, processing and data architecture,
- Excellent proficiency in processing data; including Data Mining, Clustering, Data Modeling, and Data Summarization,
- Familiarity with Data Exploratory, Predictive analysis, Regression, Text Mining and Qualitative Analysis based on business requirements.
It's always a good idea to include the benefits of the job the company will provide such as:
- Flexible hours to give you freedom and increase productivity
- Life insurance for you and your family members
- Work remotely in the comfort of your home
- Free Gym membership so you can stay in shape
- Fun and energetic weekly team bonding events
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