Data Scientist
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Job Description
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About the job
Description
Job Brief:
Responsible for transforming data into valuable insights that drive strategic decisions, illuminating our understanding of our customer base, supporting our customer value extraction units, and playing a pivotal role in driving growth.
Key Responsibilities - Prototype and build models from scratch, to support base management; from ideation, data extraction, data wrangling, feature engineering to algorithms selection and final “packaging”
- Apply statistical and machine learning techniques on customer data to extract meaningful insights relating to customer behavior and trends to drive marketing decision-making and strategies
- Full management of existing predictive models, including churn and propensity ones through timely, periodical runs, and ensuring the same performance levels are maintained through re-trainings and/or augmentation with new features or experimenting with refined/ different algorithms
- Communicate complex data insights to non-technical stakeholders through visualizations and reports effectively
- Continuous update of our base master views, through fusing and blending data from various sources, as they become available/ relevant
- Work closely with cross-functional teams to understand business requirements, address data-related challenges and provide data-driven solutions
- Identify opportunities for process automation and optimization within the Customer Base Management unit operations and leveraging data-driven techniques to streamline workflows and improve efficiency
- Identify and explore solutions to enhance the Customer Base Management unit’s analytical capabilities
- Support ad-hoc data extractions, complex data manipulations and advanced queries and reports
- Stay up-to-date with the latest advancements in data science, machine learning and current technologies and their applications
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Requirements
Education:
Bachelor's degree in Data Science, Statistics, Math, Operations Research, Computer Science, Software Engineering, or a related field with significant numerical and computational component to it.
Level Of Experience:
Limited Experience in pure-play data science domain, corporate analytics function or data warehouse/ data engineering areas.
Essential:
Technical Skills & Knowledge: - Excellent knowledge of predictive modeling using a variety of algorithms families. Ideally through either SAS or Python; with demonstrated projects
- Excellent knowledge of data processing and preparation, comfortable with both self-service tools (e.g. Alteryx) or script based (e.g. pandas)
- Good knowledge of databases and distributed databases architecture and concepts
- Excellent knowledge in data tabulation, summarization and visualization
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Desirable:
- Basic knowledge of deep learning
- Basic knowledge of Tensorflow
- Basic knowledge of social network analysis and graphs analytics at scale
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Certifications & Licensure
- Data science certification
- Python for data science
- SQL for data analysis
- Data analytics certification
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Essential:
Tools & Systems: - Python, especially data management and machine learning packages (e.g. pandas, scikit-learn)
- SQL Querying (preferably using SQL server or hive/impala)
- Power BI (or similar visualization tools)
- Microsoft Excel (at power query and VBA macros programming level)
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Desirable:
- SAS Enterprise Miner
- Alteryx
- Data Modeling and OLAP cubes creation modules
- Graph analysis Hadoop frameworks
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Employment Type
Full Time
