Data Scientist

4 days ago

Gurugram, India ARTH Full time

Role Overview :

We are looking for a Data Scientist with 3- 4 years of hands-on experience to join our growing tech team. This role is ideal for someone who enjoys solving complex, real-world problems across domains like finance, audio/video intelligence, and geospatial analytics. Youll work closely with product, engineering, and business teams to design, deploy, and optimize machine learning models that drive impact at scale.

Key Responsibilities :

- Build and maintain predictive models for financial risk, repayment behavior, and fraud detection.

- Develop ML solutions for audio/video analytics including speech-to-text, emotion detection, and document/video verification.

- Apply geospatial data science to improve customer targeting, field operations, and market insights.

- Containerize and deploy ML models using Docker, Kubernetes, and CI/CD pipelines following MLOps best practices.

- Write robust and maintainable code in Python, Go, and Java for model training, feature engineering, and real-time APIs.

- Ensure models perform efficiently on cloud-native architectures with scalable, real-time inference capabilities.

- Track, monitor, and retrain models using observability tools, performance metrics, and automated feedback loops.

Must-Have Skills :

- 3- 4 years of practical experience in data science or machine learning, ideally in fintech or related domains.

- Advanced programming skills in Python, Go, and Java.

- Proficiency with ML frameworks like Scikit-learn, TensorFlow, or PyTorch.

- Experience in audio/video analytics (e.g., Whisper, OpenCV, video embeddings).

- Familiarity with geospatial tools like GeoPandas, Shapely, or PostGIS.

- Hands-on experience with Docker, Kubernetes, and CI/CD workflows for model deployment.

- Exposure to MLOps tools such as MLflow, Airflow, or DVC.

- Solid understanding of SQL and NoSQL database systems.

- Ability to align technical solutions with business goals and real-world constraints.

Good-to-Have :

- Experience in credit scoring, risk modeling, or collections analytics.

- Familiarity with LangChain, VectorDBs, and LLMs for hybrid AI pipelines.

- Contributions to open-source projects or a strong GitHub portfolio.

- Awareness of AI ethics, compliance, and privacy regulations in financial systems.


(ref:hirist.tech)

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