Description

About ZS Associates: ZS is a global professional services firm that helps organizations transform how they create and deliver value. Combining deep industry expertise, advanced analytics, data science, and technology, we work with leading businesses to drive impactful decisions and measurable results. We are looking for a highly skilled and motivated Advanced Data Science Associate to join our Data Science & Analytics team in Pune. This is an exciting opportunity to apply cutting-edge machine learning and AI techniques to solve complex business challenges. Key Responsibilities: 1. Data Science & Modeling Design, build, and deploy advanced machine learning, deep learning, and predictive models to solve real-world business problems. Develop robust data pipelines and analytical workflows to ensure scalability and efficiency. Apply statistical modeling, NLP, and AI frameworks to extract insights and automate decision-making. 2. Business Problem Solving Partner with cross-functional stakeholders to understand business objectives and translate them into analytical solutions. Identify opportunities to improve performance through data-driven insights and innovation. 3. Data Engineering & Quality Develop and maintain large-scale data systems, ensuring data quality, integrity, and accessibility. Implement data validation and governance frameworks for consistent reporting and analytics accuracy. 4. Collaboration & Continuous Improvement Work closely with engineering, analytics, and business teams to deliver end-to-end analytical projects. Participate in code reviews, mentor junior analysts, and contribute to best practices in model development and deployment. Stay current with emerging technologies, tools, and techniques in AI/ML, data science, and analytics. Required Skills & Qualifications: Bachelor’s or Master’s Degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. 1–4 years of experience in data science, machine learning, or advanced analytics roles. Proficiency in Python and/or R with experience using libraries such as Scikit-learn, TensorFlow, PyTorch, NumPy, and Pandas. Strong understanding of statistical modeling, predictive analytics, and algorithm development. Experience with SQL and data visualization tools such as Tableau or Power BI. Familiarity with Java, C++, or other programming languages is an added advantage. Strong analytical mindset with attention to detail and problem-solving capabilities. Excellent communication skills and the ability to collaborate with cross-functional teams. Preferred Skills: Knowledge of Natural Language Processing (NLP) and Deep Learning techniques. Experience in data architecture, ETL processes, or big data frameworks (Hadoop, Spark). Exposure to cloud-based ML environments (AWS, Azure, GCP). Key Skills: Python | R | SQL | Machine Learning | Deep Learning | NLP | Data Analytics | Predictive Modeling | Statistical Modeling | Tableau | Power BI | Business Intelligence | Data Science | Algorithms | C++ | Java

Role and Responsibilities

• 1. Data Science & Modeling Design, build, and deploy advanced machine learning, deep learning, and predictive models to solve real-world business problems. Develop robust data pipelines and analytical workflows to ensure scalability and efficiency. Apply statistical modeling, NLP, and AI frameworks to extract insights and automate decision-making. 2. Business Problem Solving Partner with cross-functional stakeholders to understand business objectives and translate them into analytical solutions. Identify opportunities to improve performance through data-driven insights and innovation. 3. Data Engineering & Quality Develop and maintain large-scale data systems, ensuring data quality, integrity, and accessibility. Implement data validation and governance frameworks for consistent reporting and analytics accuracy. 4. Collaboration & Continuous Improvement Work closely with engineering, analytics, and business teams to deliver end-to-end analytical projects. Participate in code reviews, mentor junior analysts, and contribute to best practices in model development and deployment. Stay current with emerging technologies, tools, and techniques in AI/ML, data science, and analytics.