Data Scientist

Fluentgrid Limited; Visakhapatnam; On-site; INR 1,200,000 - 2,200,000; Full time

Job summary

Fluentgrid Limited in Visakhapatnam is seeking an experienced Data Scientist to develop and deploy AI/ML models for utility and smart city challenges. You will perform data analysis, feature engineering, and predictive modeling to generate actionable insights and drive decision-making.

The role requires strong Python/SQL, ML/DL skills, and experience with production pipelines, MLOps, and cloud-based analytics.

Qualifications

• Proficient in Python for data analysis and modeling.
• Strong SQL skills for large-scale data querying.
• Hands-on experience with ML/DL pipelines and model deployment.

Responsibilities

• Develop and deploy AI/ML models to solve utility and smart city business challenges.
• Perform data analysis, feature engineering, predictive modeling, and forecasting to generate actionable insights.
• Build, validate, and optimize machine learning and deep learning models for production use.
• Collaborate with business and product teams to translate requirements into data-driven solutions.
• Develop dashboards, visualizations, and reports to support decision-making.
• Implement MLOps best practices, including model monitoring, versioning, and retraining.
• Leverage cloud and big data technologies for scalable analytics solutions.
• Explore and implement Generative AI and LLM-based use cases to enhance products and services.
• Mentor team members and contribute to the organization's data science strategy and innovation initiatives.
• Ensure data quality, model performance, and compliance with organizational standards.

Skills

Python

SQL

Machine Learning

Deep Learning

Data Visualization

MLOps

Tools

Pandas

NumPy

Scikit-learn

PyTorch/TensorFlow

Job description

Job Title:Data Scientist

Experience: 8 Yrs

Location: Visakhapatnam

Employment Type: Full-time

Responsibilities

• Develop and deploy AI/ML models to solve utility and smart city business challenges
• Perform data analysis, feature engineering, predictive modeling, and forecasting to generate actionable insights
• Build, validate, and optimize machine learning and deep learning models for production use
• Collaborate with business and product teams to translate requirements into data-driven solutions
• Develop dashboards, visualizations, and reports to support decision-making
• Implement MLOps best practices, including model monitoring, versioning, and retraining
• Leverage cloud and big data technologies for scalable analytics solutions
• Explore and implement Generative AI and LLM-based use cases to enhance products and services
• Mentor team members and contribute to the organization's data science strategy and innovation initiatives
• Ensure data quality, model performance, and compliance with organizational standards

Mandatory Skills

• Strong Data Science expertise: EDA, data preprocessing, feature engineering, statistical analysis, hypothesis testing, model selection, validation and performance optimization
• Python & SQL: Advanced hands‑on proficiency in Python, Pandas, NumPy, SciPy, Scikit-learn and SQL for large-scale data analysis and modelling.
• Machine Learning: Strong experience in regression, classification, clustering, ensemble methods, Random Forest, XGBoost/LightGBM, anomaly detection and recommendation/predictive models.
• Predictive Analytics & Forecasting: Hands‑on experience in time-series forecasting, demand prediction, regression modelling and business KPI prediction.
• Deep Learning: Practical experience with PyTorch or TensorFlow, including model training, evaluation, tuning and deployment for NLP, computer vision or other AI use cases.
• Data Visualization & Insights: Strong ability to translate complex analytical results into actionable business insights using Power BI/Tableau/Plotly/Matplotlib and effective data storytelling.
• Production Data Science / MLOps: Experience taking models from experimentation to production, including ML pipelines, experiment tracking, model versioning, monitoring and retraining using tools such as MLflow/Kubeflow, Docker and CI/CD.

Good to Have Skills

• Generative AI / LLM: Experience with LLMs, embeddings, RAG, prompt engineering, vector databases, Hugging Face and frameworks such as LangChain/LangGraph; exposure to LLM evaluation and fine-tuning/LoRA is desirable.
• Big Data & Cloud: Experience with Spark/PySpark, Databricks and cloud AI/ML platforms such as AWS SageMaker, Azure ML or Google Vertex AI, along with exposure to large-scale data processing.
• Leadership & Problem Solving: Ability to lead Data Science initiatives, define analytical approaches, mentor data scientists, interact with business/product stakeholders and convert business problems into measurable AI/ML solutions.