Role: Data Scientist
Experience: 3-4 Years
Location: Hyderabad (Hybrid)
Tezo is seeking a highly motivated Data Scientist / AI Engineer with 3–4 years of professional experience in data science, machine learning, and AI solution development. In this role, you will design, develop, and deploy end-to-end data-driven solutions, working closely with cross-functional teams to solve complex business problems using advanced analytics and AI.
Why Join Our AI/ML Practice?
Purpose-driven: Work on projects that create meaningful impact for clients.
Collaborative: Learn and contribute in a team that values sharing ideas and teamwork.
Continuous Growth: Get mentorship, hands-on training, and exposure to cutting-edge tools.
Accountable & Trusted: Take ownership of your learning and contribute to team outcomes.
Key Responsibilities
- Collaborate with stakeholders to understand business challenges and translate them into data science problems.
- Design, develop, and optimize machine learning models (supervised, unsupervised, deep learning, NLP, etc.).
- Preprocess, clean, and analyze large structured and unstructured datasets.
- Deploy ML models into production environments using MLOps practices.
- Build data pipelines and work with engineers to ensure scalability and reliability of AI solutions.
- Conduct experiments, perform model validation, and optimize performance.
- Develop dashboards and visualizations to communicate insights to business teams.
- Mentor junior data scientists and contribute to best practices in coding, documentation, and model governance.
Required Skills
- Bachelor’s or master’s degree in computer science, Data Science, Statistics, Mathematics, Engineering, or related field.
- 3–4 years of hands-on experience in data science and AI projects.
- Strong programming skills in Python (preferred) or R, with expertise in Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.
- Solid understanding of machine learning algorithms, deep learning, NLP, and statistical modeling.
- Experience with SQL and data manipulation.
- Exposure to MLOps tools (MLflow, Kubeflow, Docker, CI/CD pipelines).
- Experience working with cloud platforms (AWS, Azure, GCP).
- Strong analytical and problem-solving skills, with the ability to translate data into actionable insights.
- Experience with large language models (LLMs) and generative AI.
