Overall Experience: 7+ years

Work mode: Hybrid/ Remote

About the role:

Cybage Software is looking for a highly analytical and solution-oriented Data Scientist to design, develop, and deploy scalable AI/ML and automation solutions for global clients and leading brand portfolios.

This role sits at the intersection of data science, advanced analytics, automation, and emerging agentic AI systems, helping transform complex business challenges into impactful, production-ready solutions.

You will work closely with architects, engineers, analytics teams, and business stakeholders to build intelligent systems that drive measurable business outcomes.

Key Responsibilities:

Design and develop scalable Data Science, Machine Learning, and automation solutions.
Build predictive models, analytical frameworks, and intelligent workflows using modern DS/ML techniques.
Explore and apply emerging technologies in AI, automation, agentic AI, and data enrichment.
Perform data preparation, feature engineering, hypothesis testing, experimentation, and model evaluation.
Translate business problems into robust analytical solutions and actionable insights.
Work with large-scale, multi-source datasets while ensuring data quality, governance, and reliability.
Collaborate with engineering teams to productionize models and automation pipelines.
Monitor model performance, troubleshoot issues, and continuously optimize solutions.
Communicate technical findings and recommendations effectively to both technical and non-technical stakeholders.

Required Skills & Experience:

4+ years of experience in Data Science, Applied Analytics, or ML Engineering.
Strong hands-on experience with: Python (Pandas, NumPy, Scikit-learn, SciPy, Statsmodels), SQL and large-scale data handling, Statistical modelling and Machine Learning techniques
Experience with: Data preparation and feature engineering, Predictive modelling and experimentation, Automation workflows and AI-driven analytics, Git/version control and collaborative development workflows
Understanding of modern AI/GenAI concepts such as: LLMs, RAG pipelines, Agentic AI workflows, Intelligent automation
Experience with audience analytics, customer insights, or marketing analytics is preferred.
Familiarity with data visualization and reporting platforms beyond Power BI/Tableau.
Strong problem-solving, communication, and stakeholder management skills.
Bachelor's or Master's degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or related quantitative fields.

Good to Have:

Exposure to AWS, Azure, or GCP.
Experience with MLOps, CI/CD, or production model deployment.
Knowledge of data governance, data quality frameworks, and platform integration practices.

Data Scientist – AI, ML & Agentic Automation