Associate Data Scientist

Associate Data Scientist

JOB SUMMARY

We are seeking a highly motivated Associate Data Scientist to join our growing Artificial Intelligence and Automation team. The ideal candidate will have a strong foundation in statistics, machine learning, Python, and data-driven problem solving. This role provides an excellent opportunity to work on impactful analytics and AI initiatives — from exploratory data analysis and predictive modeling to experimentation, Generative AI, and enterprise decision support.

The candidate will collaborate with cross-functional teams to translate business questions into data-driven insights and models that drive measurable value across multiple domains.

KEY RESPONSIBILITIES

• Perform exploratory data analysis, data cleaning, and feature engineering on structured and unstructured data.
• Build, validate, and interpret machine learning and statistical models (regression, classification, clustering, forecasting).
• Design and analyze experiments and A/B tests to measure impact and inform business decisions.
• Translate business problems into analytical approaches and communicate findings through clear visualizations and storytelling.
• Develop dashboards and reports to track KPIs, business metrics, and model performance.
• Support the development of Generative AI and LLM-based analytics use cases.
• Write efficient SQL and Python to extract, transform, and analyze data from enterprise sources.
• Collaborate with data engineers, ML engineers, and business stakeholders to operationalize models and insights.
• Document methodology, assumptions, and results, and ensure the reproducibility of analyses.
• Conduct research on emerging data science techniques, tools, and best practices.
• Participate in code reviews, peer reviews, and knowledge-sharing sessions.

REQUIRED QUALIFICATIONS

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related field.
• 0-2 years of experience in Data Science, Analytics, Machine Learning, or related areas.
• Strong programming skills in Python and working knowledge of SQL.
• Solid understanding of statistics, probability, and core machine learning concepts (supervised and unsupervised learning).
• Experience with data manipulation and analysis using Pandas and NumPy.
• Familiarity with data visualization techniques and tools.
• Knowledge of data structures, algorithms, and software engineering fundamentals.
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent communication skills, with the ability to explain technical results to non-technical audiences.

PREFERRED SKILLS

• Experience with Scikit-learn, statsmodels, TensorFlow, or PyTorch.
• Familiarity with visualization tools such as Power BI, Tableau, matplotlib, seaborn, or Plotly.
• Exposure to Generative AI and Large Language Models (LLMs) such as OpenAI, Anthropic Claude, Azure OpenAI, or Gemini.
• Understanding of experimentation, A/B testing, and causal inference.
• Familiarity with cloud platforms (Azure, AWS, or Google Cloud) and Databricks/Spark.
• Knowledge of MLOps concepts including model deployment, monitoring, and version control.
• Understanding of Git and collaborative development workflows.
• Experience working on data science academic, internship, personal, or open-source projects.

WHAT YOU'LL GAIN

• Hands-on experience with enterprise-scale analytics and AI initiatives.
• Opportunity to work on machine learning, Generative AI, and advanced analytics.
• Exposure to cloud-native data platforms and MLOps practices.
• Mentorship from experienced data science and technology leaders.
• Opportunity to contribute to impactful, data-driven business transformation.