Data Scientist

<h2>About the opportunity</h2> <p>We are looking for a <strong>Data Scientist</strong> who will turn data into insights and build models that drive meaningful business outcomes. You will work closely with cross-functional stakeholders to understand problems, design analytical solutions, and deploy data products that scale.</p> <h2>What to expect?</h2> <ul> <li>Collect, clean, and analyze structured and unstructured data.</li> <li>Develop predictive models, statistical analyses, and machine learning algorithms.</li> <li>Build dashboards, reports, and data visualizations to communicate insights.</li> <li>Collaborate with engineering to deploy models into production environments.</li> <li>Perform exploratory data analysis (EDA) to identify trends and opportunities.</li> <li>Conduct A/B testing and design experiments to measure feature performance.</li> <li>Document methodologies and ensure reproducibility of analytical work.</li> <li>Contribute to end-to-end machine learning workflows, including model training,&nbsp; validation, and deployment, working with established tools and patterns and with support from engineering.</li> <li>Monitor model performance and data quality, and update models as needed.</li> </ul> <h2>What do you need to be successful?</h2> <h3><strong>Required</strong></h3> <ul> <li>Bachelor’s or Master’s in Data Science, Computer Science, Statistics, Mathematics, or related field.</li> <li>Strong proficiency in <strong>Python</strong> (pandas, scikit-learn, NumPy).</li> <li>Experience using <strong>SQL</strong> to work with analytical databases and data warehouses.</li> <li>Solid understanding of <strong>statistical modeling</strong>, model evaluation, and experimental methods.</li> <li>Familiarity with machine learning techniques (regression, classification, clustering, etc.).</li> <li>Hands-on experience building and running <strong>machine learning models in production or production-like environments</strong>.</li> <li>Experience building dashboards with tools like Tableau, or similar.</li> <li>Strong analytical and problem-solving skills.</li> <li>Ability to balance analytical rigor with practical delivery.</li> <li>Excellent communication skills with the ability to translate data insights into business actions.</li> </ul> <p><strong>Preferred</strong>&nbsp;&nbsp;&nbsp;&nbsp;</p> <ul> <li>Familiarity with <strong>workflow orchestration or model lifecycle tools</strong> (e.g., Airflow, MLflow) at a practical, working level.</li> <li>Implement <strong>practical model deployment approaches</strong> (e.g., batch inference, scheduled retraining) using existing team tools and patterns.</li> <li>Experience with cloud platforms (AWS, or similar).</li> <li>Knowledge of ML Ops tools (MLflow, Airflow, or similar).</li> <li>Exposure to big data technologies (Redshift, Snowflake).</li> <li>Experience working in agile environments.</li> </ul> <h2>What's in it for you?</h2> <ul> <li>Join an ambitious tech company reshaping the way people build digital experiences</li> <li>Full-time employees receive Stock Options for the opportunity to share in the success of our company</li> <li>Comprehensive healthcare package covering 100% of monthly health premiums for employees and 85% of costs for your dependents.&nbsp;</li> <li>Fertility and family building benefits, including a lifetime reimbursable wallet to support your growing family.</li> <li>We value<strong> Work-Life balance </strong>and<strong> You Time</strong>!<strong> </strong>A generous amount of paid time off, including vacation days, sick days, compassion days for loss,&nbsp; education days, and volunteer days</li> <li><strong>Company paid parental leave</strong> to care for and focus on your growing family&nbsp;</li> <li>Use your personal annual education budget to improve your skills and grow in your career</li> <li>Enjoy a full range of virtual and in-person events, including workshops, guest speakers, and fun team activities, supporting learning and networking exch ... (truncated, view full listing at source)