Description :
We are seeking a hands-on and results-driven Data Science Specialist with 5-10 years of experience in designing and implementing advanced analytical solutions. The ideal candidate will have strong statistical foundations, demonstrated expertise in solving real-world business problems using Machine Learning, Data Science, and a track record of building and deploying data products. Exposure to NLP and Generative AI will be considered an advantage.
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 that 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 : :
Bachelor's degree in a quantitative field such as Statistics, Computer Science, Mathematics, Engineering, or a related discipline is required.Masters degree or certifications in Data Science, Machine Learning, or Applied Statistics is a strong plus.Experience :
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, and maintainable.Nice-to-Have Skills :
Experience with survival analysis or time-to-event modelling techniques.Exposure to Natural Language Processing (NLP) methods (e.g., tokenization, embeddings, sentiment analysis).Familiarity with Generative AI technologies (e.g., LLMs, transformers, prompt engineering).Experience with MLOps tools, pipeline orchestration (e.g., MLflow, Airflow), or cloud platforms (AWS, GCP, Azure).(ref : hirist.tech)