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Data Science Director Responsibilities
This Data Science Director is responsible for delivering the use case roadmap and leading exploratory analyses to identify trends that will drive value for the business, allocating critical resources, and monitoring the performance based on KPIs. It involves generating and supervising analytical approaches/models to optimize data-driven findings.
The job scope includes:
- Establishing data science project plans to enable the strategy and roadmap, and supervising ongoing data science projects utilizing required methodologies such as time-series analyses, hypothesis testing, and causal analyses.
- Leading and managing advanced and non-routine data science projects including origination, qualification, collection of data, data cleaning, and results validation in close collaboration with the respective business owners.
- Developing a comprehensive understanding of data structures and metrics, advocating for changes where needed for both platform development and data analytics.
- Supporting the Executive Director DnT to drive the fundamental shift in how business decisions can be made based on data science findings to deliver increased value and business outcomes, driving overall enterprise revenue growth.
- Leading and coaching the data scientist.
- Working with counterparts in the data technology and data intelligence department to drive business decisions by managing exploratory data analyses.
- Building strong internal and external networks to reinforce the relationship between counterpart departments and ensure cross-learning opportunities.
- Developing and maintaining good relationships with both external and internal stakeholders.
- Effectively leading and motivating teams with diverse skills and backgrounds.
- Providing constructive on-the-job feedback/coaching to team members to foster an innovative and inclusive team-oriented work environment.
- Demonstrating the ability to quickly assimilate new knowledge.
Qualifications
To be considered for the role, you will need to have:
- Master’s degree in Computer Science/Engineering or any relevant field or equivalent work experience accepted.
- 5+ years of relevant experience within a particular area of expertise in Data Science, Machine Learning, AI, etc.
- Strong problem-solving skills with an emphasis on product development.
- Advanced knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, and their real-world advantages/drawbacks).
- Profound understanding of the current and future technology trends and their interoperability, especially in business analytics and decision-making methodologies.
- Experience in manipulating, processing, and extracting value from large, disconnected datasets.
- Excellent ability to collaborate effectively with different teams.
- Excellent written and verbal communication skills.
- Proficiency in programming with Python, R, or similar programming language.
- Proficiency in Microsoft Azure stack and the corresponding data analytic and data management tools such as DataBricks, AzureML, ADF, ADLS, etc.
- Proficiency in distributed databases and query languages such as SQL or HQL (Snowflake).
Preferred Qualifications
It would be good to have:
- PhD in Machine Learning or any AI related field will be beneficial.
- Profound knowledge of advanced statistical techniques, Machine Learning and concepts (regression, properties of distributions, statistical tests and proper usage, and experience with application).
- Advanced knowledge in relevant data techniques, including statistical methods, distributed databases, query languages, etc.
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