Data Scientist - Python (Remote)

Applicants typically experience a three‑step interview process: an initial technical screening, a detailed coding and model design interview, followed by an HR round focused on cultural fit. Questions often revolve around model evaluation, dataset creation, and real‑world problem solving. Demonstrating clear communication and strong coding practices helps candidates stand out.

Round 1: Technical screening → Round 2: Technical interview (model design & coding) → Round 3: HR interview

Artha.link fosters a collaborative, growth‑oriented culture where remote teams thrive on autonomy and continuous learning. Employees enjoy flexible work hours, regular virtual meetups, and ample opportunities for skill development.

Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or related field. Minimum 60% marks in the qualifying exam. No backlogs allowed. Candidates from 2025, 2026, or 2027 batches are encouraged to apply.

Hire Feed, a leading AI‑driven recruitment platform, is partnering with a global technology leader to bring cutting‑edge talent solutions to the market. The company leverages advanced machine learning models to match candidates with the right opportunities, streamline hiring workflows, and provide actionable insights to recruiters worldwide. With a focus on innovation, Hire Feed has built a reputation for delivering high‑quality, data‑driven solutions that transform the recruitment landscape. The Data Scientist – Python (Remote) role is a full‑time position that offers the chance to work on real‑world AI applications from anywhere in the world. As a key member of the data science team, you will design, develop, and maintain efficient Python code to train and optimize AI models. Your work will directly influence the performance of the platform’s recommendation engine, natural language understanding modules, and reinforcement learning pipelines. Key Responsibilities: 1. Design and implement scalable Python solutions for training and fine‑tuning machine learning models. 2. Conduct rigorous evaluations to benchmark model performance and analyze results. 3. Evaluate and rank AI model responses across diverse domains to ensure alignment with business criteria. 4. Develop comprehensive explanations and rationales for evaluation outcomes. 5. Lead supervised fine‑tuning initiatives, creating high‑quality, task‑specific datasets. 6. Collaborate with researchers, annotators, and product teams to incorporate human feedback into reinforcement learning workflows. 7. Debug production code, resolve performance bottlenecks, and maintain robust technical documentation. 8. Communicate findings clearly in Jupyter notebooks and stakeholder presentations. 9. Stay updated on the latest research in NLP, deep learning, and reinforcement learning. 10. Mentor junior team members and share best practices. Tech Stack: Python, PyTorch/TensorFlow, scikit‑learn, Jupyter, Git, Docker, AWS/GCP. Growth Path: Starting as a Data Scientist, you can progress to Senior Data Scientist, Lead Data Scientist, or AI Research Lead, with opportunities to influence product strategy and lead cross‑functional teams. Why Join? You’ll work with a global leader, contribute to high‑impact AI solutions, and enjoy a flexible remote work environment that values innovation, continuous learning, and work‑life balance.