Lead Data Scientist
Geekhunter is hiring on behalf of our client, an innovative corporate food and cloud kitchen management company, in partnership with the most exciting food brands. The company provides delicious, fresh, and creative food solutions for everyday corporate and group needs. They give a new spin on food facility management and their signature MICE catering, delivering a noteworthy experience while helping corporates manage costs.
Our client is an affiliate of a group corporation which is the leading brand in the Lifestyle Food & Beverage company with more than 70 outlets operating across Indonesia, Singapore, Shanghai, and Dubai. With more than 15 years of culinary experience, the company truly understands the art of creating affordable high-quality food.
- THR, BPJS-K and BPJS-TK
- Private Health Insurance & Medical Reimbursement
- Laptop Ownership Program
- Flexible Working Hour
- Leveraging large amounts of user data
- Collect, transform and model data from various sources
- Build predictive models to help figure out what the users need
- Have direct contribution to optimize models, drive insights for business and product teams to bring more impacts for business and customers
- Help build the data team
- Define detailed scope and methodology, creating and executing on the framework with appropriate modelling techniques, translating business context into relevant analysis
- Have more than 3-4 years of experience working in a similar role in Data, and at least 1 year in a leading role
- Able to translate business problems into data science solutions
- Intermediate level in Python or Scala or any programming language in Data Science
- Proficiency in using query languages such as SQL, Hive, etc.
- Experience with NoSQL databases, such as MongoDB, Cassandra, HBase and Relational Database such as MySQL, PostgreSQL
- Experience with working in GCP (or any other cloud solution)
- Experience understanding and translate business needs into data models (predictive modelling), creating logical and physical data models using best practices to ensure high data quality and reduce redundant information.
- Have deep or understanding on Big data platform (Hadoop, Spark, Kafka, etc.)
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