Interview Process
- 3 rounds of internal technical interviews- One face-to-face mandatory interview included
- No client round (as of now)
Key Responsibilities
- Build and deploy RAG (Retrieval-Augmented Generation) systems & AI chat interfaces
- Work closely with client data science teams (ML/DL ecosystems)
- Develop GenAI-based enterprise knowledge solutions
- Collaborate directly with stakeholders and customers
Mandatory Skills
- Strong experience in:
- Machine Learning (ML)
- Deep Learning (DL)
- Hands-on experience with:
- Generative AI (LLMs, RAG systems)
- Exposure to:
- Claude / Anthropic-based development (or similar GenAI tools)
- Strong communication & client-facing capability
Good to Have
- Basic exposure to:
- Domain experience in:
- Oil & Gas / Energy sector
Tech Environment
- AWS ecosystem
- Snowflake (data platform)
We are looking for a Senior Data Scientist with a strong traditional ML/DS background and hands-on experience in GenAI (LLMs, RAGs, Agentic workflows). The candidate should not be purely academic or junior; we need someone with practical implementation experience and the ability to interact confidently with customers. Strong communication and product-facing exposure are equally important.
Tavant Technologies is seeking a Senior Data Scientist for our Enterprise Products team. In this role, you will leverage advanced analytical techniques and machine learning methods to derive actionable insights from complex datasets. Your primary responsibilities will include developing predictive models, analyzing data to identify trends, and collaborating with cross-functional teams to implement data-driven solutions that enhance our enterprise product offerings.
Key Responsibilities:
- Develop and implement machine learning algorithms to solve complex business problems.
- Analyze large datasets to generate insights and inform decision-making processes.
- Collaborate with product managers and engineers to integrate data science solutions into enterprise products.
- Communicate findings and recommendations effectively to technical and non-technical stakeholders.
- Stay current with the latest advancements in data science and machine learning technologies.
Skills and Tools Required:
- Strong proficiency in programming languages such as Python or R.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Solid understanding of statistical analysis techniques and data modeling.
- Proficiency in data visualization tools (e.g., Tableau, Power BI).
- Familiarity with big data technologies (e.g., Hadoop, Spark).
- Ability to work with databases and query large datasets using SQL.
- Strong problem-solving skills and the ability to think critically.
- Excellent communication and collaboration skills.
Preferred Qualifications:
- A master's or Ph.D. in computer science, statistics, mathematics, or a related field.
- Experience in the tech industry or with enterprise-level software products.
- Understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud).
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