Data Scientist - Connected vehicle (Remote)

<div><span><h3><strong>Job Title:</strong> Data Scientist</h3><div><strong>Experience:</strong> 6+ Years<br><strong>Location:</strong>&nbsp; Remote</div><hr><h3><strong>Company Overview</strong></h3><div>At Codvo, software and people transformations go hand-in-hand. We are a global empathy-led technology services company. Product innovation and mature software engineering are part of our core DNA. Respect, Fairness, Growth, Agility, and Inclusiveness are the core values that we aspire to live by each day.</div><div>We continue to expand our digital strategy, design, architecture, and product management capabilities to offer expertise, outside-the-box thinking, and measurable results.</div><h3><strong>About the Role:</strong></h3><div>We are looking for an experienced <strong>Data Scientist</strong> to drive the development of data-driven solutions in the <strong>connected vehicle analytics</strong> domain. The ideal candidate will have deep expertise in <strong>predictive modeling, machine learning, and data visualization</strong>, with a strong focus on delivering actionable insights that enhance vehicle performance, driver behavior, and operational efficiency.</div><hr><h3><strong>Key Responsibilities:</strong></h3><ul><li><strong>Model Development:</strong> Design, build, and validate <strong>predictive models</strong> for connected vehicle analytics, including driver behavior analysis, vehicle health monitoring, and route optimization.</li><li><strong>Data Exploration:</strong> Analyze and interpret large, complex datasets to uncover patterns, correlations, and actionable business insights.</li><li><strong>Feature Engineering:</strong> Identify and engineer key features to improve model performance and accuracy.</li><li><strong>Model Optimization:</strong> Collaborate with the AI Lead to fine-tune models, test new algorithms, and assess performance metrics.</li><li><strong>Visualization &amp; Insights:</strong> Develop clear and insightful dashboards and visual reports using tools like <strong>Power BI</strong> or <strong>Looker</strong> to communicate findings to stakeholders.</li><li><strong>Collaboration:</strong> Work closely with data engineering and product teams to operationalize models and integrate insights into decision-making systems.</li><li><strong>Continuous Improvement:</strong> Stay up to date with advancements in machine learning, data processing, and automotive data analytics to enhance solution capabilities.</li></ul><hr><h3><strong>Skills &amp; Qualifications:</strong></h3><ul><li><strong>Education:</strong> Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.</li><li><strong>Technical Expertise:</strong><ul><li>Proficient in <strong>Python</strong> (pandas, numpy, scikit-learn, etc.).</li><li>Hands-on experience with <strong>machine learning and deep learning frameworks</strong> such as TensorFlow, PyTorch, or Keras.</li><li>Strong understanding of <strong>statistics</strong>, <strong>probability</strong>, and <strong>data modeling techniques</strong>.</li><li>Experience in <strong>feature engineering, model evaluation, and hyperparameter tuning</strong>.</li><li>Skilled in <strong>data visualization</strong> and storytelling using <strong>Power BI</strong> or <strong>Looker</strong>.</li><li>Exposure to <strong>cloud-based data environments</strong> (AWS, Azure, or GCP) is a plus.</li></ul></li><li><strong>Soft Skills:</strong><ul><li>Analytical and problem-solving mindset with attention to detail.</li><li>Strong communication skills for presenting technical results to non-technical audiences.</li><li>Ability to work independently and collaboratively in cross-functional teams.</li></ul></li></ul><hr><h3><strong>Preferred Experience:</strong></h3><ul><li>Experience working with <strong>connected vehicle data</strong>, <strong>IoT telemetry</strong>, or <strong>mobility analytics</strong>.</li><li>Knowledge of <strong>data pipelines</strong> and <strong>real-time analytics</strong> frameworks.</li></ul></span></div>