Role Overview :
We are seeking a highly skilled and motivated Senior Data Scientist with 3-5 years of experience in Artificial Intelligence (AI) and Machine Learning (ML). The ideal candidate will be responsible for driving end-to-end problem-solving initiatives, from understanding the problem to developing predictive and prescriptive models, deploying solutions, and effectively communicating insights to stakeholders. Experience in time-series analysis and CAD / CAE will be considered a strong plus.
Key Responsibilities :
Problem Understanding :
- Collaborate with cross-functional teams to identify and understand business challenges.
- Translate business problems into analytical tasks and define the problem scope.
Data Exploration and Preparation :
Collect, clean, and preprocess large datasets from multiple sources.Perform exploratory data analysis (EDA) to extract meaningful insights.Model Development and Time-Series Analysis :
Design, develop, and optimize AI / ML models to solve complex problems.Apply advanced techniques to analyze and forecast time-series data.Implement end-to-end machine learning pipelines, from data ingestion to deployment.Deployment and Scalability :
Build and deploy machine learning models into production environments.Ensure scalability, robustness, and efficiency of deployed models.Implement MLOps practices for model lifecycle management.Communication :
Present technical findings and actionable insights to non-technical stakeholders.Create visualizations and reports to communicate results effectively.Continuous Improvement :
Stay updated with the latest advancements in AI / ML technologies.Experiment with new tools and techniques to enhance model performanceExperience :
3 - 5 years of hands-on experience in AI / ML model development, deployment, and lifecycle management.Qualifications :
Bachelors or Masters degree in Computer Science, Data Science, Statistics, or related fields.Required Skills :
Proficiency in programming languages like Python.
Strong knowledge of machine learning algorithms, deep learning frameworks (e.g.,TensorFlow, PyTorch), and optimization techniques.
Experience working with time-series data analysis and forecasting techniques.Expertise in deploying models using cloud platforms (AWS, GCP, Azure) and containerizationtools (e.g., Docker, Kubernetes).
Excellent communication and presentation skills to convey complex ideas clearly.(ref : hirist.tech)