<p><strong>What role you will play in team:</strong> You will be a crucial member of our data science team, contributing to the development and implementation of machine learning models for improved business decision-making. You will collaborate closely with other data scientists, engineers, and business stakeholders.</p><p><strong>What you will do:</strong> You'll be involved in the entire data science lifecycle, from data collection and preprocessing to model building, evaluation, and deployment. You'll work on a variety of projects that leverage cutting-edge machine learning techniques. </p><p><strong>Key responsibility:</strong><ul><li>Collect, clean, and preprocess large datasets.</li><li>Develop and implement machine learning models.</li><li>Evaluate model performance and identify areas for improvement.</li><li>Deploy models into production environments.</li><li>Collaborate with other data scientists and engineers.</li><li>Communicate findings to business stakeholders.</li><li>Stay up-to-date with the latest advancements in machine learning.</li></ul></p><p><strong>Required Qualification and Skills:</strong><ul><li>Bachelor's degree in a quantitative field (e.g., computer science, statistics, mathematics).</li><li>Proficiency in Python or R.</li><li>Experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).</li><li>Strong analytical and problem-solving skills.</li><li>Excellent communication skills.</li><li>Experience with SQL and big data technologies (e.g., Hadoop, Spark) is a plus.</li></ul></p><p><strong>Benefits Included:</strong><ul><li>Competitive salary and benefits package.</li><li>Opportunities for professional development.</li><li>Collaborative and supportive work environment.</li><li>Health Insurance, Paid Time Off.</li><li>Retirement Plan</li></ul></p><p><strong>A Day in the Life:</strong> You'll start your day by reviewing the progress of your current projects, collaborating with team members, and then diving into data analysis and model building. You'll spend a significant part of the day coding and experimenting with different machine learning algorithms, and then you'll present your findings to stakeholders.</p>