Data Scientist/Analyst

Turing’s interview process typically consists of a 60‑minute technical round focusing on Python coding, data‑analysis case studies, and model‑evaluation concepts, followed by a 15‑minute cultural round that assesses communication skills and alignment with the company’s values. Candidates should be ready to discuss past projects, solve live coding problems, and demonstrate clear reasoning.

Turing promotes a fully remote culture that values autonomy, continuous learning, and rapid iteration. Employees receive regular mentorship, clear growth tracks, and a supportive environment that balances challenging projects with work‑life flexibility.

Bachelor’s or Master’s degree in Engineering, Computer Science, Mathematics, Statistics or a related field. Minimum 60% academic record (or equivalent CGPA). Open to graduates from the 2025‑2027 batches. No backlogs allowed at the time of joining. Strong foundation in data analysis, statistical modeling, and Python programming is required.

Round 1: Technical coding and data‑analysis assessment → Round 2: System design & evaluation methodology discussion → Round 3: HR / cultural fit interview

Turing is one of the world’s fastest‑growing artificial‑intelligence companies, dedicated to accelerating the development and deployment of powerful AI systems. By partnering with leading AI labs, Turing pushes the boundaries of frontier model capabilities such as reasoning, multimodality, and multilingual understanding. The company then translates these breakthroughs into real‑world solutions that address mission‑critical problems for enterprises across the globe. The organization operates fully remotely, giving its talent the freedom to work from anywhere while collaborating with top‑tier AI researchers and product teams in the United States. Turing’s culture emphasizes rapid innovation, continuous learning, and a strong focus on ethical AI alignment. Employees enjoy exposure to cutting‑edge large language models (LLMs) and the chance to contribute to products that shape the future of human‑computer interaction. **Role Summary** The Data Scientist/Analyst will join a high‑impact team that designs, builds, and refines AI models for commercial and research customers. The role blends strong Python programming with deep data‑analysis skills to extract insights from public datasets, create high‑quality training data, and evaluate model performance. Clear communication with researchers, annotators, and cross‑functional stakeholders is essential, as is the ability to document reasoning and code in Jupyter notebooks or similar environments. **Key Responsibilities** - Design, develop, and maintain efficient Python code for training and optimizing AI models. - Conduct systematic evaluations (Evals) to benchmark model performance and generate improvement reports. - Rank and analyze AI model responses across diverse domains, ensuring alignment with predefined criteria. - Write detailed explanations and rationales for evaluation outcomes, showcasing strong reasoning. - Lead Supervised Fine‑Tuning (SFT) initiatives, building and curating task‑specific datasets. - Collaborate with researchers and annotators to implement Reinforcement Learning with Human Feedback (RLHF) and refine reward models. - Invent innovative evaluation strategies to improve model alignment with user needs and ethical guidelines. - Produce and polish optimal model responses, emphasizing clarity, relevance, and technical accuracy. - Perform peer reviews of code and documentation, offering constructive feedback. - Work closely with cross‑functional teams to drive product enhancements and model performance gains. **Tech Stack**: Python, Jupyter Notebook, Pandas, NumPy, Scikit‑learn, PyTorch, TensorFlow, SQL, Git, Docker. **Growth Path**: Junior Data Scientist → Data Scientist → Senior Data Scientist → AI Lead → AI Architect/Principal Engineer. **Why Join Turing**: Remote‑first work model, exposure to state‑of‑the‑art LLM projects, mentorship from world‑class AI researchers, and the chance to shape next‑generation AI products while enjoying flexibility and competitive compensation.