Solutions Engineer (Data Science - Python)

ClanX

Requirements:

5+ YOE with programming languages such as Python, R, and SQL
5+ YOE in data science or related field
Experience with data visualization tools such as Tableau, Power BI, etc
Experience working with Cloud Platforms such as Google Cloud, AWS, etc

Responsibilities:

Analyze large and complex data sets using statistical analysis
Create dashboards and reports to communicate insights to stakeholders
Lead the development of data-driven strategies that guide our business decisions
Act as the technical POC between the company and customers, guiding them through the integration process with our platform
Oversee customer support issues, providing resolutions

Interview Process:

First Technical Round
Second Technical Round
Final Round (Tech + Culture) with Senior Leadership

Job Details:

CTC Range: Rs. 30 to Rs 35 LPA
Job Type: Fulltime - Remote

Benefits:

Competitive salary and equity package
Comprehensive health, dental, and vision insurance
Unlimited vacation time and flexible work hours
Professional development opportunities
Fun and collaborative work environment

Company Details
A cutting-edge AI-driven hybrid cloud cost management solutions VC backed US-based startup, specializing in delivering
innovative solutions that enable businesses to monitor, analyze, and optimize their cloud costs and usage.

We are inviting you to answer a few questions. You have the opportunity to practice, and you will have UNLIMITED retakes available for different questions. Good luck!

P.S. Got Questions? Contact [email protected]

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Answer these questions to complete the application:

How many years of experience do you have in Data Science?
What is your current CTC? (in Lakhs)
What is your expected CTC? (in Lakhs)
Are you available to join within 30 days?
What is your notice period (days)?
Help us with your resume
Can you discuss a challenging data science project where you applied advanced machine learning algorithms or statistical analysis? Highlight your specific contributions, the outcomes, and how you addressed any data challenges.
Describe your experience with training and fine-tuning GPT models. What specific models have you worked with, and what were the objectives and results of one of these projects?
What tools and languages do you prefer for data analysis and visualization, and why? Please provide an example of how you've used Python, R, or SQL along with a tool like Tableau or Power BI to solve a complex problem or present data insights effectively
Tell me about a time when you led a data science team or project. What were the project goals, how did you manage the team, and what were the key decisions you made that influenced the project’s success?
What approach do you take when creating predictive models, particularly for forecasting or anomaly detection? Please share a detailed example, including the data you used, the model development process, and how the model's performance was evaluated
This role requires communication with the clients, are you open for the same?
Please mention your LinkedIn profile

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