Data Scientists work on problems that are core to the company’s mission, build and develop the company’s core technologies. Data scientists provide decision support analysis for many teams across the organization, including product development, sales, marketing, and strategy. Data scale ranges from small data sets to large multi-terabyte data in distributed database systems.
In your first 30 days, you will:
- Onboard with Data science team, set up your dev environment, get access to data systems and become familiar with the tech stack
- Learn about on-going initiatives involving data scientists, product managers, and engineers
- Spend time with members of the Analytics, scrum teams and learn how our teams collaborate
- Become familiar with the data landscape and hit the ground running by joining a project team
In your first 60 days, you will:
- Get familiarized with various data we are having and will gather.
- Learn how to use and navigate our various databases and write scripts using our data for various analyses
- Learn about our existing code-base and best practices
- Collaborate with other data scientists to help build our products
In your first 90 days, you will:
- Integrate into long-term multi-data-scientist ventures and deliver on one or several short-term individual projects
- Perform analyses that help us better understand end-users, while helping you get familiarized with our data
- Spend time with sales and marketing team to learn about the world of retail and farming
- Develop an understanding of both immediate business objectives as well as longer-term company aspirations to develop intuition around prioritization and trade-offs between short-term deliverables and longer-term R&D efforts
- Develop creative solutions to diverse problems including engineering challenges, unstructured data messes, ontology development, and machine learning applications.
- Performing data mining, statistical analysis, and operationalization of analytical models.
- Lead and develop major projects from end-to-end encompassing planning, design, technical implementation, debugging, roll-out to Product & Engineering, testing, and iteration.
- Collaborates with business segments to extract analytical, behavioral and predictive insights from ever-increasing data resources. Applies progressive statistical, programmatic, and analytical approaches to business hypotheses to gain deeper understanding of available data.
- Responsible for the design, development, and maintenance of analytical models that will be placed into operation. Will be required to explore internal and external data sources to identify useful structures within the data that were/are previously unknown to the business. Should have a strong understanding of relational and dimensional modeling to facilitate data wrangling, model operationalization, and exploration of data.
- Evaluate and experiment with new technologies and tools prior to wider adoption by the team.
- Operate at the level of sophistication in statistics, machine learning, or computer science that is publication-worthy.
- Regularly monitor pull requests, perform code reviews, and produce excellent peer reviews on projects prior to shipping to Product & Engineering.
- Work closely with analysts, data scientists, product managers, and engineers.
- Minimum 1 year of industry production experience as a Data Engineer
- Excellent verbal communications, including the ability to clearly and concisely articulate complex concepts to both technical and non-technical collaborators
- Degree(s) should be in a technical discipline such as Computer Science, Engineering, Statistics
- Similar to SQL relational databases as well as big data: the Hadoop ecosystem, Spark
- Required: SQL, Python, Linux shell scripting
- Desired: Keras, TensorFlow, Spark SQL, Python
- Similar to machine learning and computational statistics packages
- Similar to visualization tools
- Frequent user of cloud computing platforms such as Amazon Web Services, Microsoft Azure, IBM Watson Studio, IBM Private and Hybrid Cloud or Google Cloud Platform
- Bonus Points: previous work on data analytics
Quantity needed: 01
Interested candidates please send your applications to: firstname.lastname@example.org. Application documents include: