Understand the business requirements to understand the problems to solve.
Work with a data analyst to ensure data is available in the required structure and format.
Analyze data to discover trends and patterns using statistical techniques.
Develop algorithms and / or models to transform data into useful, actionable information.
Present information using data visualization techniques.
Help define best practices and standards for data engineering at the organization.
What you must have :
Very strong proficiency in Python and / or R.
Very strong proficiency with data architecture and best practices.
Strong problem-solving and analytical skills.
Knowledge of statistics and experience using statistical packages for analyzing datasets
Data wrangling.
Experience using business intelligence tools (e.g. Power BI, Incorta) and data frameworks (e.g. Hadoop).
Understanding of analytical models and how to structure data for model usage.
Experience doing feature engineering and topic modelling.
Experience doing the following types of analysis : text analysis, comparative analysis, trend analysis, sentiment analysis.
Excellent communication and presentation skills.
Strong multi-tasking skills, with an ability to adapt to and manage changing priorities.
Ability to work within a team environment or independently as needed.
Ability to manage your time efficiently and work with little supervision.
Ability to manage stress in an environment with high expectations, tight deadlines and changing priorities.
Understanding best practices, methods, and standards for business intelligence, analytics, and visualizations.
Agile Methodologies.
Team Foundation Server (TFS) - Code Management
SQL Server Experience.
Knowledge of SQL.
Experience analyzing and transforming survey data.
Machine Learning.
Predictive Analytics.
Pension administration knowledge.
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