Website:
xenvolt.ai
Job details:
Company Description
Xenvolt AI empowers enterprises to address complex governance challenges by transforming traditional systems into a predictive, transparent, and adaptive framework. By leveraging AI-powered insights and real-time intelligence, we enable organizations to anticipate risks, ensure compliance, and optimize operations. Our solutions drive smarter decision-making, promote accountability, and support sustainable growth. At Xenvolt, we are committed to helping businesses navigate challenges and unlock their full potential.
About the Role
Xenvolt Technologies is looking for a motivated and detail-oriented Data Scientist to join our growing Data Science team. The candidate will work on real-world machine learning and data analytics problems involving forecasting, predictive analytics, monitoring systems, and AI-driven applications.
This role offers an opportunity to work on end-to-end ML workflows, data-driven product development, and scalable AI solutions across industrial and renewable energy domains.
Key Responsibilities
- Build, train, and evaluate machine learning models for predictive analytics and forecasting applications.
- Perform data preprocessing, feature engineering, and exploratory data analysis.
- Develop and optimize time-series forecasting models.
- Work with structured and unstructured datasets from multiple sources.
- Collaborate with software and product teams for deployment and integration of ML solutions.
- Monitor model performance and improve accuracy through experimentation and tuning.
- Create visualizations, dashboards, and analytical reports for insights and decision-making.
- Participate in research and implementation of AI/LLM-based solutions where applicable.
Required Skills
- Strong proficiency in Python.
- Hands-on experience with Pandas, NumPy, Scikit-learn, XGBoost, Matplotlib and Seaborn.
- Understanding of machine learning concepts and model evaluation techniques.
- Experience with SQL and NoSQL database handling.
- Knowledge of time-series forecasting techniques.
- Familiarity with feature engineering and data preprocessing pipelines.
- Understanding of statistics and probability concepts.
Preferred Skills
- 1–2 years of hands-on experience in Data Science, Machine Learning, or AI-based projects.
- Experience with Deep Learning frameworks such as TensorFlow or PyTorch.
- Exposure to cloud platforms or model deployment workflows.
- Familiarity with APIs, FastAPI/Flask, or ML integration pipelines.
- Exposure to Generative AI or LLM-based applications is a plus.
- Experience working with IoT, industrial, or renewable energy datasets is advantageous.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, or related fields.
Why Join Us?
- Opportunity to work on impactful real-world AI projects.
- Collaborative and innovation-driven work environment.
- Hybrid working flexibility.
Click on Apply to know more.