
P99Soft - Senior Data Scientist - Machine Learning Models
1 day ago
Description :
We are looking for a highly experienced Senior Data Scientist to join our analytics and machine learning team.
This role requires a seasoned professional who can drive the end-to-end lifecycle of machine learning models from data exploration and feature engineering to production deployment and ongoing model management.
The ideal candidate has a strong foundation in predictive analytics, hands-on experience building scalable ML solutions in production, and a knack for translating complex data insights into clear, actionable business recommendations.
Key Responsibilities :
- Design, develop, and deploy robust machine learning models and predictive analytics solutions to solve complex business challenges.
- Lead the full ML lifecycle: data acquisition, cleaning, feature engineering, model selection, training, evaluation, deployment, and monitoring.
- Collaborate closely with cross-functional teams including engineering, product management, and business stakeholders to align ML solutions with business objectives.
- Develop and maintain scalable, production-grade machine learning pipelines using tools such as Airflow, Docker, and MLflow.
- Build automated workflows for model retraining, validation, and deployment in cloud environments such as Azure ML, AWS SageMaker, or Google Cloud AI Platform.
- Utilize advanced statistical techniques including regression analysis, time-series forecasting, and anomaly detection to inform decision-making.
- Conduct rigorous experimentation including A/B testing to evaluate model performance and impact on key business metrics.
- Define and track success metrics and KPIs to continuously optimize models and strategies.
- Provide clear and compelling data-driven storytelling and presentations to both technical and non-technical audiences.
- Mentor junior data scientists and contribute to the development of best practices within the team.
- Stay current with emerging trends in machine learning, data science, and AI to continuously innovate and improve methodologies.
Required Qualifications :
- 8+ years of hands-on experience in data science, with demonstrated success building and scaling ML models beyond prototypes or research projects.
- Strong proficiency in Python and SQL, with expertise in ML libraries such as scikit-learn, XGBoost, LightGBM, TensorFlow, and PyTorch.
- Deep understanding of predictive modeling techniques, including regression, classification, time-series forecasting, and feature engineering.
- Experience working with large datasets and cloud platforms including Azure, AWS, or GCP; hands-on experience with managed ML services such as Azure ML or SageMaker.
- Practical knowledge of workflow orchestration tools like Apache Airflow and containerization using Docker.
- Expertise in experiment design and analysis, including A/B testing and statistical hypothesis testing.
- Ability to translate complex technical concepts into clear business insights and communicate effectively across teams.
- Experience in relevant domains such as finance, commodities trading, retail pricing, or demand forecasting is highly desirable.
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