Data Scientist
Sensor Tower Inc.
1 month ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
IntermediateJob location
Remote
Tech stack
Query Performance
Microsoft Excel
Data analysis
Spreadsheets
Databases
Data Mining
Data Structures
Data Visualization
Python
Machine Learning
Raw Data
Ruby
Jupyter Notebook
Information Technology
Job description
WHAT YOU WILL WORK ON
- Prototype machine learning models in Python or Ruby.
- Analyze query performance to ensure calculation efficiency.
- Write tests for the implementation of machine learning models.
- Collaborate with back-end engineers to understand the raw data being collected.
- Collaborate with front-end engineers to create data visualizations for both external and internal customers.
- Conduct ad-hoc data analysis based on requests from the Sales, CSM or Contents team.
- Present results of various data analysis.
Requirements
Code, Python, Mathematics, Analytics, Databases, Deliveries, Steps, Mastery, Data Science, Computer Science, Data Mining, Statistical Modeling, Business Intelligence, Excel, Ruby, Statistics, Scratch, * Master's degree or above in mathematics, statistics, or computer science.
- 3+ years applied experience in business intelligence, data mining, analytics, or statistical modeling in technology or mobile industries OR 2+ years applied experience in data science in mobile market intelligence.
- Ability to write code that is ready for production (Python and Ruby preferred).
- Experience with adjusting data for bias.
- Substantial experience with databases, querying data, and data structure manipulation.
- Ability to communicate effectively with technical developers and non-technical marketing business partners.
- Ability to produce rough timelines for deliveries plus solid understanding of steps necessary to complete a project.
- Ability to come up with a rough project structure from scratch.
- Ability to critically analyse given data, ask probing questions, and perform own research.
- Substantial knowledge of statistical modeling techniques.
- Mastery of one or more statistical visualization or graphing toolkits such as Excel, Jupyter Notebooks, or Google Spreadsheets.