data scientist
Confidential Company
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Job benefits
Flexible work hours
Productivity curve is not something steady and consistent as it depends on each person's unique traits and preferences. At our company, as long as your team is in sync and your goal is hit, you can flexibly decide when you want to work.
Medical insurance
To ensure your health and wellbeing, you have various medical plans to choose from depending on your situation and unique needs. From partial up to full medical coverage, we got you covered.
Skills
Job description for data scientist:
1. Develop and deploy analytical solutions across a variety of business functions, including, but notlimited to: customer acquisition, customer retention, product development, pricing decisions, creditrisk, fraud identification and many other business needs within Digibank for both retail and wholesalebanking customers
2. Uncover and deliver insights and trends to deliver actionable product recommendations to support thebusiness, through dashboards and advanced visualization techniques,
3. Creating data products which can be readily used by partners and business units across the bank.
4. Partner closely with the broader product, engineering and marketing teams to define requirements,design and analyze experiments that drive key product designs and marketing decisions.
5. Develop analytic tools to help the data team and other disciplines be more effective in debugging,data summarization and analysis of results
6. Conduct both historical and predictive analyses and convert into digestible, readable, and publicly-available insights.
7. Ensure data accuracy and good segmentation of data sets for tactical data mining
Must-have requirements for data scientist:
1. Bachelors or Masters degree in Statistics, Analytics, Economics, Mathematics, Engineering or otherquantitative subjects
2. Extensive hands-on experience with tools such as Python, R, Presto, SQL/Hive, and DataVisualization platforms like Tableau/ Power BI/D3.js
3. Solid experience in reporting to CEO / directors in delivering analyses and reports
4. Extensive expertise in data modeling, both logical and physical
5. Experience with designing, running and analyzing A/B tests and product experiments. Should alsohave an understanding of hypothesis testing and the basic principles of DoE
6. Expertise in data retrieval, data modeling, data warehouse design, and predictive modeling
7. Passionate about solving problems – possesses a relentless need for investigation and dataexploration.
8. Results and detail-oriented, with strong intuitions on how to solve problems creatively and quickly.
9. Ability to distill data and articulate an actionable point of view to non-technical audiences and seniorstakeholders using presentations, interactive visualizations, et al.
