Data Scientist
1 month ago
Role : Data Scientist
Job description :
- Write well documented code that can be shared and used across teams, and can scale to be used in existing products. SQL, Advanced Python or R (descriptive / predictive models), Tableau Visualization.
- Working knowledge of Hadoop, BigQuery, Presto, Vertica
- Apply your expertise in quantitative analysis, data mining, and the presentation of data to uncover unique actionable insights about customer service, health of public conversation and social media
- Inform, influence, support, and execute analysis that feeds into one of our many analytics domains Customer analytics, product analytics, business operation analytics, cost analytics, media analytics, people analytics
- Select and deselect analytics priorities, insights and data based on ability to drive our desired outcomes
- Own the end to end process, from initiation to deployment, and through ongoing communication and collaboration, sharing of results to partners and leadership
- Mentor and create sense of community and learning environments for our global team of data analysts
- Experiment and Develop: You will drive the end to end machine learning project lifecycle using best practices and well managed software delivery
- Work on proof of concepts and experiments to demonstrate value ML can bring basis product requirements
- Documenting data requirements, data collection, processing, cleaning and exploratory data analysis
- Collaborate across teams for timely well managed deliverables
- Innovate, Share and Educate team members and community
Soft skills :
- Ability to communicate findings clearly to both technical and non-technical audiences and to effectively collaborate within cross-functional teams
- Working knowledge of agile framework and processes.
- You should be comfortable managing work plans, timelines and milestones
- You have a sense of urgency, move quickly and ship things
Bonus Points :
- You are experienced in metrics and experiment-driven development
- Experience in statistical methodology (multivariate, time-series, experimental design, data mining, etc.)
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