Brief Description of position:

About Aryng :

• Aryng is a Data Science consulting, training and advising company. Aryngs SWAT Data science team helps solve complex business problems, develop the companys Data DNA through Data Literacy programs and deliver rapid ROI using machine learning, deep learning, and AI. Our client list includes companies like Google, Box, Here, Applied Materials, Abbott Labs, and GE among others.
• Are you overworked and have no work-life balance?
• Are you frustrated with writing queries but having no clue if your work is driving any impact?
• Are you a downstream order taker with no access to clients or stakeholders?
• Are you tired of your company's work culture with useless hierarchy and bureaucracy?
• Are you constantly in a support role with no seat at the table?

At Aryng, we are looking for analytics thought leaders who want to drive impact with their direct hands-on work with the client. This is a permanent job role in a fast-growing start-up with fantastic work culture and excellent job satisfaction.
Aryng is a Silicon-Valley based data science consulting company with clients including Google, JMSMuckers, Regeneron, GE, Life360, and Ipsy.

Here are our core values:

1. We have a non-hierarchical, super transparent culture. We all know what everyone is working on, where we are going, and how we are doing.
2. We are all learners, entrepreneurial, and love growth.
3. We are super talented and are known in the industry as a SWAT data science team

10 Reasons to Join Aryng :

a. Direct Client Access
b. Flexible Working Hours
c. Rapidly Growing Company
d. Awesome Work Culture
e. Learn From Experts
f. Work-life Balance
g. Competitive Salary
h. Executive Presence
i. End to End Problem Solving
j. 50%+ Tax Benefit

Impact driving work | Awesome work culture | Flexible work hours | Great pay| Direct client access

Job Description: 

Conduct data science experiments, deploy models, monitor, and maintain machine learning and deep learning systems. Take ownership of Machine Learning systems -- from data pipelines and experimentation to deployment and real-time prediction. 

Collaborate with the data science and analytics team to understand business objectives and operationalize data science solutions. 

Monitor ML / DL model in deployment for data drift or concept drift; create strategies to combat such problems. 

Conduct cost benefit analysis of different deployment strategies. 

Improve existing model functionality through distributed systems and parallel processing architecture. 

Work with clients and stakeholders, to help them understand the benefits, timeline, and scope of the project. 

Expected skills:

Proficiency with core Python and familiarity with libraries for machine learning and data pre-processing. 

Proficiency with SQL and RDB concepts. 

Experience in working with bash , powershell and batch files for automation. 

Good grasp of Git for version control. Familiarity with either Github, Gitlab or Bitbucket. 

Experience with developing and deployment of models with cloud infrastructure
(AWS, GCP, AZURE) and with on-premise infrastructure

Excellent communication and presentation skills.

Good to have:

Familiarity with a deep learning framework such as TensorFlow or Keras and experience with deploying such models. 

Experience with technologies like Spark, Hadoop, Kafka. 

Experience with Docker and Kubernetes for containerization.