Track This Job
Add this job to your tracking list to:
- Monitor application status and updates
- Change status (Applied, Interview, Offer, etc.)
- Add personal notes and comments
- Set reminders for follow-ups
- Track your entire application journey
Save This Job
Add this job to your saved collection to:
- Access easily from your saved jobs dashboard
- Review job details later without searching again
- Compare with other saved opportunities
- Keep a collection of interesting positions
- Receive notifications about saved jobs before they expire
AI-Powered Job Summary
Get a concise overview of key job requirements, responsibilities, and qualifications in seconds.
Pro Tip: Use this feature to quickly decide if a job matches your skills before reading the full description.
Data Science & Analytics
- Explore, clean, and analyze structured and unstructured datasets.
- Apply statistical techniques to generate insights and support business decisions.
- Develop predictive models using regression, classification, clustering, NLP, or time-series methods.
- Conduct hypothesis testing, A/B experiments, and exploratory data analysis (EDA).
- Build, train, and fine-tune ML models using frameworks such as TensorFlow, PyTorch, Scikit-learn.
- Develop and maintain end-to-end ML pipelines, including feature engineering, model training, evaluation, and versioning.
- Deploy ML models into production using MLOps pipelines and tools like MLflow, Kubeflow, SageMaker, or Vertex AI.
- Implement monitoring, retraining strategies, and improve model performance.
- Optimize models for scalability, latency, and resource efficiency.
- Requirements
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, AI/ML, or related field.
- 3–7+ years of experience as a Data Scientist, ML Engineer, or similar role.
- Strong programming skills in Python (NumPy, Pandas, Scikit-learn, Matplotlib, etc.).
- Experience with ML frameworks (TensorFlow, PyTorch).
- Strong understanding of machine learning algorithms, statistics, and data modeling.
- Experience deploying models in production (Docker, APIs, cloud deployment).
- Knowledge of SQL and experience with relational and NoSQL databases.
- Familiarity with MLOps tools (MLflow, Kubeflow, Airflow, DVC)
Key Skills
Ranked by relevanceReady to apply?
Join Tek Tron IT and take your career to the next level!
Application takes less than 5 minutes

