Associate - Data Scientist

Job Description:

Responsibilities

• As an Associate Data Scientist, you will complete data science projects that create customer strategies, sustainable revenue and share growth, efficiencies and cost savings
• Assist in ad-hoc decision support, analytics projects, and scenario analyses
• Gather and organize data from various sources using SQL/Python
• Develop and validate predictive models using Python and SQL. Also, interpret model outputs and communicate insights to stakeholders

Qualification & Experience 

• Master’s degree in data science or relevant fields like Statistics, Engineering, Computer Science, Operational Research or a related STEM field
• 0–1 year of experience in data science, data manipulation, or analytical work
• Proficiency in Python and SQL for data analysis and problem-solving
• Hands-on experience working with Jupyter Notebook or similar Python-based IDEs
• Experience querying and manipulating relational databases using tools such as Microsoft SQL Server, Oracle SQL Developer, Teradata SQL Assistant, or similar
• Basic familiarity with machine learning concepts such as regression, classification, bagging, boosting, and common evaluation metrics (e.g., accuracy, precision, recall)
• Awareness of Generative AI concepts such as prompt engineering and Retrieval-Augmented Generation (RAG)
• Strong problem-solving skills with solid analytical and logical thinking abilities
• Proficient in Microsoft Excel and PowerPoint for analysis and presentation
• Strong interpersonal, written, and verbal communication skills
• Fluent in English (written and spoken)
• Legally authorized to work in India for any employer without sponsorship
• Successful completion of the interview process is required to meet job qualifications
• Reliable and punctual attendance is an essential function of the role
• What will help you propel from the pack (Preferred Qualifications):
• Awareness of advanced Generative AI concepts, including Agentic AI
• Basic familiarity with cloud platforms or cloud-based data environments (e.g., AWS, Azure, GCP) is a plus