Data Scientist

2 weeks ago

Bengaluru Chennai Hyderabad, India Tiger Analytics Full time ₹ 15,00,000 - ₹ 20,00,000 per year

Role & responsibilities

As a Data Scientist, your work is a combination of hands-on contribution to Loreum Ipsum, Loreum Ipsum, etc. More specifically, this will involve:

Analytical Translation: Translate complex business problems into sophisticated analytical structures, conceptualising solutions anchored in statistical and machine learning methodologies.

Problem Solving: While technical proficiency in data manipulation, statistical modelling, and machine learning is crucial, the ability to apply these skills to solve real-world business problems is equally vital.

Client Engagement: Establish a deep understanding of clients' business contexts, working closely to unravel intricate challenges and opportunities.
• Algorithmic Expertise: Develop and refine algorithms and models, sculpting them into powerful tools to surmount intricate business challenges.

Quantitative Mastery: Conduct in-depth quantitative analyses, navigating vast datasets to extract meaningful insights that drive informed decision-making.

Cross-Functional Collaboration:Collaborate seamlessly with multiple teams, including Consulting and Engineering, fostering relationships with diverse stakeholders to meet deadlines and bring Analytical Solutions to life.

What do we expect?

  1. 2 -7 years of Relevant Data Science Experience, with demonstrated proficiency and hands-on experience navigating data science complexities.

  2. Mandatory : Minimum 2+ years of experience in the Banking and Financial services industry

  3. Good communication skills, both verbal and written.

  4. Exhibit a fervour for crafting modular, scalable, and bug-free Python code.

  5. Comfortable in SQL with additional proficiency in office tools like Excel & PowerPoint.

  6. Experience in production engineering best practices (e.g. Git versioning, Docker).

  7. Familiarity or experience with working on large data sets and distributed computing (e.g. Hive, Hadoop, Spark)

  8. Working knowledge of Cloud platforms (e.g. AWS, Azure, GCP).

  9. Excitement to collaborate with diverse stakeholders across the organisation.

  10. In-depth understanding of various data science approaches, machine learning algorithms, and statistical methods.

  11. Hunger to learn new technologies and embrace the change. Proficiency in foundational concepts and algorithms in machine learning, encompassing regression and classification techniques, and a keen awareness of their assumptions, strengths, and limitations.

  12. Must-Have Skills: Regression/Classification/Optimization/ Python Proficiency in these key skills is crucial to thriving in this

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