Data Scientist/Analyst

Turing’s interview process typically consists of a 60‑minute technical round focused on Python, data manipulation, and AI concepts, followed by a brief cultural and offer discussion. The questions are moderately challenging, emphasizing practical problem‑solving and clear communication. Candidates should practice coding on platforms like LeetCode and be ready to explain their reasoning in Jupyter notebooks.

Turing promotes a fully remote, results‑oriented culture where engineers enjoy flexibility and autonomy. Employees receive regular feedback, mentorship from senior AI researchers, and clear pathways for skill advancement, while maintaining a healthy work‑life balance through flexible hours and a supportive community.

Bachelor’s or Master’s degree in Engineering, Computer Science, Mathematics, Statistics or related field; minimum 60% aggregate (or CGPA 6.5/10); fresh graduates or candidates from batch 2023‑2026; no active backlogs; strong command of English (both written and spoken).

Round 1: Technical interview (60 minutes) covering Python, data analysis, and AI concepts → Round 2: Cultural fit & offer discussion (15 minutes) → Round 3: HR/contract finalization (if required)

Turing is a rapidly expanding AI‑focused company that partners with world‑leading research labs to push the boundaries of artificial intelligence. By blending cutting‑edge research with real‑world product development, Turing helps global enterprises adopt advanced AI solutions across domains such as natural language processing, computer vision, and multimodal reasoning. The firm’s culture emphasizes autonomy, continuous learning, and a results‑driven mindset, allowing engineers and scientists to work on high‑impact projects while collaborating with top talent from around the globe. As a Data Scientist/Analyst at Turing, you will be part of a dynamic team that builds, evaluates, and refines large language models for US‑based clients. The role blends rigorous data analysis with hands‑on model development, requiring you to write clean, well‑documented Python code, explore public datasets (Kaggle, UN, US government portals), and translate business questions into actionable insights. You will also interact closely with researchers, annotators, and product managers to ensure that model outputs align with user expectations and ethical standards. Key responsibilities: 1. Design, develop, and maintain high‑quality Python pipelines for training and fine‑tuning AI models. 2. Conduct systematic evaluations (Evals) to benchmark model performance and generate detailed analysis reports. 3. Rank and assess model responses across diverse domains, ensuring alignment with predefined quality criteria. 4. Create clear, logical explanations for evaluation outcomes, documenting reasoning in Jupyter notebooks. 5. Lead supervised fine‑tuning (SFT) efforts, curating and maintaining task‑specific datasets. 6. Collaborate on Reinforcement Learning with Human Feedback (RLHF) loops and reward‑model refinement. 7. Propose and implement innovative evaluation strategies to improve model alignment and safety. 8. Review peer code and documentation, offering constructive feedback. 9. Work with cross‑functional teams to integrate model improvements into product releases. 10. Stay abreast of emerging tools, techniques, and research trends to continuously enhance the training workflow. Tech stack: Python, Pandas, NumPy, Scikit‑learn, PyTorch/TensorFlow, Jupyter, SQL, Git, Docker, cloud platforms (AWS/GCP), data visualization libraries (Matplotlib, Seaborn, Plotly). Growth path: Starting as a contractor, high performers can transition to full‑time roles, lead larger AI projects, specialize in model alignment, or move into senior research or product leadership positions. Turing’s remote‑first policy ensures exposure to global clients and cutting‑edge AI challenges, making it an ideal launchpad for ambitious data professionals. Why join Turing? You will work on frontier AI technology from the comfort of your home, gain mentorship from world‑class researchers, and earn a competitive compensation package while contributing to products that shape the future of intelligent systems.