Data Scientist
Data Scientist
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
Collaborate with cross-functional teams and clients to define data-driven solutions to real-world business problems.
Design and develop machine learning models (classification regression clustering recommendation systems etc.) using structured and unstructured data.
Conduct thorough exploratory data analysis (EDA) and statistical testing to identify patterns trends and actionable insights.
Perform feature engineering data transformation and selection to optimize model performance.
Evaluate validate and fine-tune models using techniques like cross-validation A/B testing and performance metrics (e.g. F1-score ROC-AUC RMSE).
Prepare end-to-end pipelines for model development training validation and testing using Python and ML libraries (e.g. Scikit-learn XGBoost TensorFlow).
Deploy ML models to production using Flask FastAPI or cloud-based solutions (e.g. Azure ML AWS Sagemaker GCP AI Platform).
Monitor model performance post-deployment and implement re-training strategies as needed.
Work on NLP computer vision or time-series forecasting projects as per client requirements.
Stay up to date with the latest developments in Data Science ML and AI and proactively suggest innovative solutions for business problems.
Create clear documentation and present complex model outputs and insights in a simple interpretable manner to both technical and non-technical stakeholders.
Contribute to the standardization of data science frameworks reusable assets and best practices across projects.
Requirements
4 to 5 years of hands-on experience in a Data Scientist role
Strong proficiency in Python Libraries required for ML (NumPy Pandas Scikit-learn Tensorflow Pyspark etc.)
Good experience with SQL and working with relational databases
Experience in building and evaluating predictive models and other machine learning models (supervised and unsupervised learning etc.)
Knowledge of EDA feature engineering and data preprocessing
Experience with Data Visualization - Power BI Tableau or Python-based visualization libraries
Experience working on cloud platforms (Azure AWS or GCP) is preferred
Familiarity with model deployment techniques (Flask FastAPI Docker MLflow)
Strong communication skills and experience working in client-facing environments
Ability to manage multiple projects and meet tight deadlines
Benefits
Working hours: 10:00 AM 7:00 PM
Working days: 5 days a week (plus 1st & 3rd Saturdays working)
Medical Insurance coverage for employees
Provident Fund (PF) facility
Quarterly parties and yearly outings/trips for team bonding
Regular check-ins with leadership for growth and feedback
Recognition awards to celebrate high performance
Python Libraries EDA Feature Engeenering Power BI Tableau Cloud Platforms
Education
Bachelor s or Master s degree in Computer Science, Data Science, Statistics, or a related field Experience in service-based project environments (handling multiple clients/projects)
Employment Type
Full Time
