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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.