Key Responsibilities
Collect, clean, and analyze large structured and unstructured datasets.
Build, train, and validate predictive, classification, and generative models using ML and deep learning frameworks.
Identify and create optimal input variables to improve model performance.
Communicate insights effectively using data visualization tools and dashboards.
Partner with engineers to deploy AI models into production and ensure scalability.
Stay updated with emerging trends in AI/ML, big data technologies, and advanced analytics.
Translate analytical findings into actionable recommendations for stakeholders.
Required Skills
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch), SQL; familiarity with R is a plus.
Experience in supervised/unsupervised learning, NLP, and deep learning architectures.
Knowledge of big data tools (Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
Proficiency in Tableau, Power BI, or similar tools.
Strong analytical thinking and structured problem-solving approach.