Data Scientist II
- Bengaluru, India
At Amazon, we strive to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them an environment in which they can relentlessly improve the experience for customers. Innovation and creativity are built into the DNA of the company and are encouraged at all levels of employment. Every day we solve complex technical and business problems with ingenuity and simplicity. We're making history and the good news is we've only just begun.
The ideal candidate will have extensive experience in Data Science work, business analytics and have the aptitude to incorporate new approaches and methodologies while dealing with ambiguities in sourcing processes. Excellent business and communication skills are a must to develop and define key business questions and to build data sets that answer those questions.
As a Data Scientist in the team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the Fulfilment Centre operations. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organisational standards.
The Data Scientist will be accountable for:
1. Creating and delivering roadmap of the most challenging ML business problems from operations and use data to articulate possible root cause analysis and solutions.
2. Building world class statistical and machine learning models which will solve operational challenges
3. Working closely with Business Intelligence Engineers and developing the Machine learning expertise within the team by supervision.
4. Drive actions at scale to provide high impact services using scientifically-based methods and decision making and driving a low cost to serve.
5. Utilising Amazon systems and tools to effectively work with terabytes of data.
6. Providing inputs and recommendations on technical issues to Business Intelligence engineers.
You will also have the opportunity to display your skills in the following areas:
1. Design, build and own all the components of a high volume data warehouse end to end.
2. Interface with other technology teams to extract, transform, and load (ETL) data from a wide variety of data sources
3. Build efficient data models using industry best practices and metadata for ad hoc and pre-built reporting
4. Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions
5. Design, implement, and support a self-service platform providing ad hoc access to large datasets
6. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
7. Interface with business customers, gathering requirements and delivering complete reporting solutions
• Masters in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
• 5+ years of experience working in data science in a consumer product company.
• 1+ years of experience mentoring Machine Learning Scientists, Data Scientists, Research Scientists.
• Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
• Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes
• Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
• Experience on reporting platform such as Quicksight /Tableau
• Experience in at least one modern object-oriented programming language (Python, Java, Ruby, R)
• Experience leading a Team .
• Experience with Agile development methodologies
• Experience with AWS services including S3, Redshift, EMR, Kinesis and RDS.
• Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)
• Experience with building pipelines from application databases.
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