Data Science Engineer
Strong Data Analytical Skills, ability to find patterns and build prediction models, data monetization techniques, Python/R and SQL/NOSQL, data visualization, data models Business Intelligence, problem-solving, strong communication
Who Are We?
Skayle is a leading AI-driven Consumer Engagement and Predictive Analytics SaaS platform to Engage Customers, Gain Insights, Predict Behaviours, and Increase Sales for the F&B industry. It’s cloud-based platform is designed to simplify and streamline the CRM functions of running a successful restaurant by providing true closed loop, customer lifecycle marketing, off-line to online targeting and business intelligence.
Skayle started as a small team of 6 people and has since grown to a team of 150 people in 7 offices in Asia, Australia and America. Today, over 700 brands in nine countries use Skayle’s solutions to improve interaction with customers and boost revenues. Its proprietary platform has engaged over 12.3 million consumers in 9 countries and has powered more than 5 million in-store reviews.
Who Are You?
You are responsible for providing analytical insight to business owners & key stakeholders and presenting recommendations to clients and influencing product roadmap based on insights. The ideal candidate will have great problem-solving skills, and good hands-on experience with Python/R, ETL Processes, SQL queries and databases, and should be able to generate visualizations, analytical reports, presentations etc.
- Build predictive models and machine-learning algorithms.
- Provide analytical insight to business owners and key stakeholders.
- Often being the lead owner of a report or advanced analytics projects.
- Lead the Data Science Team to come up with solutions for various business problems.
- Work with the Engineering team for Product Improvements and Changes.
- Design, plan and execute project related tasks.
You Will Own
- Critical thinking, specifically the ability to hear a business need and determine the best way to solve the problem using available data and analytics.
- Utilize data analytics and advanced data science techniques to identify trends, patterns, and discrepancies in data. Determine additional data needed to support insights.
- Monitor company membership counts, trends, etc. and notify appropriate party when anomalous activity occurs.
- Present information using data visualization techniques and tools.
- Collaborate with engineering and leadership teams.
- Present recommendations to clients and influencing future plans based on insights.
- Document procedures, processes and workflows.
- Drive projects through various stages, work with internal and external teams to successfully navigate landscape.
- Strong knowledge of Python/R, SQL, advanced analytics (ML & NLP), and business intelligence.
- Experience analyzing data and sharing results in a non-analytical format, “telling the story”.
- Knowledge of BI tools like Tableau, Qlik Sense, Data Studio and Kibana.
- Familiarity with Elastic DB is a bonus.
- Familiarity with Google Cloud Platform & Amazon Web Services.
- Familiarity with machine learning and predictive models.
- Github and JIRA project experience ideal.
- Some exposure to NLP (Natural Language Processing).
- Excellent verbal and written communication skills.
- Ability to adapt to new development environment, changing business requirements and learning new systems.