ML Engineer

Cynepia Technologies

1 - 3 Years
2 Openings
3.0 - 5.0 Lac/Yr
Face-to-Face interview
Bangalore

Key Skills

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Job Description

We are changing the way enterprises manage and consume data and insights by making data and insights platform smarter and better. As part of Cynepia Technologies, Customer Facing Data Scientists are critical to making our customers successful.

An ideal candidate should have strong fundamentals of applied data science in a business setting and should enjoy communicating and evangelizing data science solutions to business stakeholders.

He must possess an understanding of the following :

A) Product/Customer/People Skills :

1. Someone who has been working for a fast-paced started environment in the capacity as an individual contributor and is focused on understanding customer problems/requirements and solving the same using Cynepia Products/Solutions that address the same.

2. Executing data engineering/science workflows for customers

3. Conducting and managing data science projects with customer's vision of success in mind.

4. Engaging and collaborating with various customer teams and managing experience.

5. Great oral and written communication and hunger to create and build is not negotiable.

6. Strong customer interaction, management and organizational skills.

B) Technical Skills :

1. Experience with dataset preparation using python/R.

2. Experience building and optimizing data pipelines, architectures and data sets.

3. Hands-on experience building predictive models and preparing data for the same.

4. Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Understand and write code that adheres to and ensures serviceability, performance, reliability, availability and scalability of the architecture in a large enterprise

5. Prior Experience working with the adoption of enterprise data products/use cases in a fast-paced startup environment desired.

6. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.