We are seeking a highly skilled and experienced Senior Data Scientist to lead the development and deployment of advanced data-driven solutions.
The ideal candidate will have strong expertise in machine learning, statistical modeling, and data engineering, combined with the ability to translate complex data insights into actionable business strategies.
This role requires hands-on technical skills, leadership capabilities, and a passion for solving challenging problems with data.
Key Responsibilities :
- Lead end-to-end data science projects, from problem definition and data collection to modeling, evaluation, and deployment.
- Apply advanced statistical and machine learning techniques to develop predictive, prescriptive, and descriptive models.
- Collaborate with business stakeholders to understand challenges and design data-driven solutions that align with business goals.
- Work closely with data engineers to ensure data availability, quality, and scalability of data pipelines.
- Conduct exploratory data analysis (EDA) to extract insights and identify opportunities for optimization and growth.
- Develop, validate, and optimize machine learning models for real-world deployment.
- Communicate findings clearly and effectively to both technical and non-technical stakeholders through presentations, reports, and visualizations.
- Mentor junior data scientists and analysts, fostering a culture of learning and innovation within the team.
- Stay up to date with emerging technologies, algorithms, and tools in the field of AI, ML, and data science.
- Drive experimentation and innovation to continuously improve models and methodologies.
Required Skills & Qualifications :
Masters or PhD in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.610 years of proven experience as a Data Scientist with expertise in developing and deploying ML models.Strong programming skills in Python and experience with ML / DL libraries such as Scikit-learn, TensorFlow, PyTorch, and XGBoost.Proficiency in SQL and experience with large-scale data handling.Deep understanding of statistical methods, hypothesis testing, and experimental design.Hands-on experience with cloud platforms such as AWS, Azure, or GCP for model deployment.Strong problem-solving, critical thinking, and analytical skills.Excellent communication skills with the ability to explain technical concepts to non-technical audiences.Preferred Qualifications :
Experience with big data technologies (Spark, Hadoop, Databricks).Knowledge of MLOps practices, including model versioning, CI / CD for ML, and monitoring.Familiarity with business domains such as finance, e-commerce, healthcare, or telecommunications.Strong publication record, participation in Kaggle competitions, or contributions to open-source projects(ref : hirist.tech)