Data Scientist, Regression + Genai + Nlp
3 weeks ago
Tiger Analytics is a global AI and analytics consulting firm. With data and technology at the core of our solutions, our 3900+ tribe is solving problems that eventually impact the lives of millions globally. Our culture is modeled around expertise and respect with a team-first mindset. Headquartered in Silicon Valley, you’ll find our delivery centers across the globe and offices in multiple cities across India, the US, UK, Canada, and Singapore, including a substantial remote global workforce. We’re Great Place to Work-Certified. Working at Tiger Analytics, you’ll be at the heart of an AI revolution. You’ll work with teams that push the boundaries of what is possible and build solutions that energize and inspire.
**About the role**:
**Analytical Translation**: Translate complex business problems into sophisticated analytical structures, conceptualising solutions anchored in statistical and machine learning methodologies.
- **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.
**Desired Skills and Experience**:
- 4+ years of Relevant Data Science Experience, with demonstrated proficiency and hands-on experience navigating data science complexities.
- Good communication skills, both verbal and written.
- Exhibit a fervour for crafting modular, scalable, and bug-free Python code.
- Comfortable in SQL with additional proficiency in office tools like Excel & PowerPoint.
- Experience in production engineering best practices (e.g. Git versioning, Docker).
- Familiarity or experience with working on large data sets and distributed computing (e.g. Hive, Hadoop, Spark)
- Working knowledge of Cloud platforms (e.g. AWS, Azure, GCP).
- Excitement to collaborate with diverse stakeholders across the organisation.
- In-depth understanding of various data science approaches, machine learning algorithms, and statistical methods.
- 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.
- Must-Have Skills: Regression/Classification/Optimization/ Python Proficiency in these key skills is crucial to thriving in this role.
**Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry**.
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