Responsibilities:

● Analyze large datasets and uncover valuable business insights through data mining techniques.

● Develop and deploy predictive models for various applications (e.g., customer segmentation, demand forecasting, anomaly detection).

● Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

● Design and implement data-driven models, ensuring scalability, efficiency, and accuracy.

● Perform data preprocessing and feature engineering to prepare data for analysis.

● Continuously monitor, evaluate, and optimize deployed models to improve performance.

● Stay current with the latest developments in machine learning and data science to implement best practices.

● Present findings and recommendations clearly to both technical and non-technical stakeholders.

Whatmakesyouagreat fit:

● 3-7yearsofexperience in data science or a related role.

● Provenexpertise in building, training, and deploying machine learning models.

● Solid understanding of statistical techniques, machine learning algorithms (supervised, unsupervised learning), and deep learning.

● Proficiency in Python and hands-on experience with machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.

● Strongproblem-solving skills with the ability to work with large, complex datasets.

● Excellent communication and collaboration skills to work effectively with technical and non-technical teams.

Bonus points:

● Experience with cloud platforms (AWS, GCP, Azure).

● Familiarity with big data technologies (e.g., Hadoop, Spark).

● Experience with MLOps tools and workflows.

● Knowledgeofdatavisualization tools like Tableau or Power BI