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Roles and responsibilities
- Participate in architecture design and implementation of data platform model solutions.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Use predictive modelling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
- Design and build data processing and analytics logic
- Develop processes and tools to monitor and analyse model performance and data accuracy.
- Interact with business users to gather requirements and to determine source of data elements and subsequent organization and retrieval of data from the data warehouse.
- Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Knowledge of advanced statistical techniques and concepts(regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
- Big Data Analysis
- Requirement Gathering & Analysis
- Data Integration & Segregation
- Team Management
- Experience working with and creating data architectures
- Experience with Data Visualization Tools like Domo, Tableau that help to visually encode data
- Reporting & Documentation
- Degree in Computer Science, Engineering or relevant field is preferred
- Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL is desirable.
- Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark.
- Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.
- Databases: Microsoft SQL & MySQL
- Data warehouse: Teradata, snowflake
- Operating Systems: Windows & Linux
- Other Tools: Putty & WinSCP
Good to have:
- Experience with big data tools: Hive, Spark.
- Familiarity with Scala or Java is an added advantage..
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.