Data Science Specialist

As a Data Science Specialist, your role will involve collaborating with cross-functional teams to translate business problems into data science use cases. You will design, develop, and deploy data science models, including classification, regression, and survival analysis techniques. Your responsibilities will also include building and productionizing data products that deliver measurable business impact, performing exploratory data analysis, feature engineering, model validation, and performance tuning. Additionally, you will apply statistical methods to uncover trends, anomalies, and actionable insights, while staying up to date with advancements in NLP and Generative AI to evaluate their applicability to internal use cases. Clear communication of findings and recommendations to both technical and non-technical stakeholders will be essential. Key Responsibilities: - Collaborate with cross-functional teams to translate business problems into data science use cases. - Design, develop, and deploy data science models including classification, regression, and ideally survival analysis techniques. - Build and productionize data products to deliver measurable business impact. - Perform exploratory data analysis, feature engineering, model validation, and performance tuning. - Apply statistical methods to uncover trends, anomalies, and actionable insights. - Implement scalable solutions using Python (or R/Scala), SQL, and modern data science libraries. - Stay up to date with advancements in NLP and Generative AI and evaluate their applicability to internal use cases. - Communicate findings and recommendations clearly to both technical and non-technical stakeholders. Qualifications: - Education: Bachelor's degree in a quantitative field such as Statistics, Computer Science, Mathematics, Engineering, or a related discipline is required. Master's degree or certifications in Data Science, Machine Learning, or Applied Statistics is a strong plus. - Experience: 4-5 years of hands-on experience in data science projects, preferably across different domains. Demonstrated experience in end-to-end ML model development, from problem framing to deployment. Prior experience working with cross-functional business teams is highly desirable. Must-Have Skills: - Statistical Expertise: Strong understanding of hypothesis testing, linear/non-linear regression, classification techniques, and distributions. - Business Problem Solving: Experience translating ambiguous business challenges into data science use cases. - Model Development: Hands-on experience in building and validating machine learning models (classification, regression, survival analysis). - Programming Proficiency: Strong skills in Python (Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn), and SQL. - Data Manipulation: Experience handling structured/unstructured datasets, performing EDA, and data cleaning. - Communication: Ability to articulate complex technical concepts to non-technical audiences. - Version Control & Collaboration: Familiarity with Git/GitHub and collaborative development practices. - Deployment Mindset: Understanding of how to build data products that are usable, scalable. Additional Company Details: The company values continuous learning and encourages staying updated with the latest advancements in data science technologies, fostering a culture of innovation and growth for its employees.,