Job description for Data Scientist Support at Lawencon International
Key Responsibilities
- Develop, validate, and deploy predictive and prescriptive analytics models to support business decision-making.
- Design and implement machine learning, statistical, and optimization models for real-world business use cases.
- Analyze large and complex datasets to uncover actionable insights and recommendations.
- Develop data pipelines and prepare datasets for modeling and analysis.
- Collaborate with cross-functional teams to identify business opportunities and translate them into data science solutions.
- Deploy machine learning models into production environments and monitor their performance.
- Optimize model performance through feature engineering, model tuning, and continuous improvement.
- Work with structured and unstructured data from multiple sources.
- Document methodologies, model assumptions, and technical implementations.
- Stay up to date with emerging technologies, tools, and best practices in data science and advanced analytics.
Requirements
- Bachelor's degree or Diploma in Computer Science, Data Science, Statistics, Mathematics, Information Technology, Engineering, or a related field.
- Minimum 2 years of experience in predictive and prescriptive analytics (advanced analytics) or equivalent practical experience.
- Strong proficiency in SQL, NoSQL, and related database technologies.
- Proficiency in Python and/or R for machine learning, statistical modeling, and operations research.
- Hands-on experience with machine learning, statistical modeling, and/or operations research techniques.
- Experience deploying machine learning models into production environments using MLOps or related deployment practices.
- Experience with big data technologies such as Apache Spark, Hive, Impala, Kafka, or similar platforms is highly preferred.
- Proven experience implementing advanced analytics solutions in business or enterprise projects.
- Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.
- Excellent analytical, problem-solving, and communication skills.
- Ability to work independently and collaboratively in a multidisciplinary team.
