Job Title : Data Scientist AI/ML & Advanced Analytics
Location : Remote / Hybrid
Experience : 5 to 8 Years
Job Overview
We are looking for a skilled Data Scientist with strong expertise in machine learning, statistical analysis, predictive modeling, and advanced analytics. The ideal candidate will work closely with Data Engineers, AI/ML Engineers, and business stakeholders to build data-driven solutions that support forecasting, risk analysis, operational intelligence, and decision-making initiatives.
Key Responsibilities
- Analyze structured and unstructured data to identify trends, patterns, risks, and actionable business insights.
- Develop machine learning, statistical, predictive, and advanced analytical models.
- Perform exploratory data analysis (EDA), feature engineering, segmentation, hypothesis testing, and model experimentation.
- Train, evaluate, tune, validate, and optimize predictive and analytical models.
- Develop analytics use cases such as forecasting, operational risk prediction, quality monitoring, performance analysis, and resource planning.
- Collaborate with Data Engineers to access governed datasets from Microsoft Fabric Lakehouse and enterprise data platforms.
- Work with AI/ML Engineers to operationalize models into APIs, dashboards, pipelines, and business workflows.
- Present analytical findings, model outputs, assumptions, limitations, and recommendations to business stakeholders.
- Support model documentation, explainability, monitoring, reproducibility, and Responsible AI practices.
- Contribute to AI-driven analytics, automation initiatives, and decision-support solutions.
Required Skills
- Strong Python programming and statistical analysis skills.
- Experience with machine learning algorithms, statistical modeling, and predictive analytics.
- Hands-on experience in EDA, feature engineering, model training, evaluation, and optimization.
- Strong SQL skills and experience working with large analytical datasets.
- Experience with libraries/frameworks such as pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch, or equivalent.
- Understanding of ML lifecycle management, experimentation practices, model documentation, and performance metrics.
- Strong analytical thinking and problem-solving capabilities.
Good To Have
- Experience with NLP, LLMs, Generative AI, RAG, embeddings, chatbot solutions, or document intelligence.
- Exposure to Microsoft Fabric Data Science, Azure Machine Learning, Azure AI Services, MLflow, Databricks, or Synapse.
- Experience in healthcare, pharma, CRO, clinical research, or life sciences analytics.
Preferred Qualification
- Bachelors/Masters degree in Computer Science, Data Science, Statistics, Mathematics, AI, or related field.
(ref:hirist.tech)
