<p>An organization operating at global scale is seeking a <strong>Senior Data Scientist</strong> to join its corporate data science team. This role goes far beyond traditional analytics—you will develop innovative data-driven technologies, advanced machine learning models, and decision‑support systems that directly influence strategic and operational outcomes across a complex aviation and logistics environment.</p><p>The ideal candidate combines strong programming capability, deep machine learning expertise, and a solid foundation in operations research, along with the ability to clearly communicate technical insights to leaders across the business.</p><p>If you’re excited about applying science, experimentation, and advanced analytics to solve real operational problems, this role is an excellent opportunity to make a measurable impact.</p><p><br></p><p><strong>Position Summary</strong></p><p>As a Senior Data Scientist, you will partner with engineering, product, and business teams to identify opportunities where data science can drive measurable value. You will lead end‑to‑end development of predictive and prescriptive models, contribute to experimentation frameworks, and help shape the organization’s long‑term data science strategy. This role also provides technical leadership and mentorship to junior data science team members.</p><p><br></p><p><strong>Key Responsibilities</strong></p><p><strong>Strategic &amp; Technical Leadership</strong></p><ul><li>Lead the planning, design, and execution of complex data science initiatives aligned with business objectives.</li><li>Translate ambiguous business requirements into well‑defined data science projects, deliverables, and timelines.</li><li>Partner with cross‑functional stakeholders to identify impactful use cases across operations and corporate functions.</li></ul><p><strong>Data Science &amp; Modeling</strong></p><ul><li>Develop predictive, prescriptive, and optimization models to enhance operational efficiency and strategic planning.</li><li>Design and run experiments to test hypotheses and measure impact using statistical methods.</li><li>Perform exploratory data analysis to uncover insights, trends, and relationships across large and complex datasets.</li><li>Build and maintain decision‑support tools powered by machine learning and operations research techniques.</li><li>Monitor model performance in production and iterate as needed.</li></ul><p><strong>Data Engineering &amp; Analysis</strong></p><ul><li>Collect, clean, and process structured and unstructured data from internal and external sources.</li><li>Perform ETL tasks, develop data pipelines, and apply advanced data preparation techniques.</li><li>Use tools such as SQL, Python, R, Pandas, Spark, or similar frameworks to analyze large datasets.</li></ul><p><strong>Communication &amp; Collaboration</strong></p><ul><li>Create compelling visualizations, dashboards, and presentations to communicate complex insights to technical and non‑technical audiences.</li><li>Provide mentorship, guidance, and subject‑matter expertise to junior data scientists.</li><li>Contribute to the evaluation and adoption of emerging technologies, modeling techniques, and industry best practices.</li></ul><p><br></p>

<p><strong>Required</strong></p><ul><li>Master’s degree or Ph.D. in Operations Research, Machine Learning, Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field</li><li><em>Bachelor’s candidates with equivalent hands‑on experience are also encouraged to apply.</em></li><li>3+ years of experience in data science or advanced analytics (6+ years for those without a graduate degree).</li><li>Strong programming skills in Python, R, or similar languages.</li><li>Proficiency in data manipulation (SQL, Pandas, Spark) and machine learning libraries (scikit‑learn, TensorFlow, PyTorch, etc.).</li><li>Deep understanding of statistical analysis, hypothesis testing, and ML modeling principles.</li><li>Experience writing production‑grade code using version control, testing, and standard software engineering practices.</li><li>Ability to work independently with limited supervision while managing complex projects.</li></ul><p><strong>Desired</strong></p><ul><li>Domain experience in aviation, transportation, or logistics.</li><li>Experience with big data tools such as Spark, Databricks, or Palantir.</li><li>Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.</li><li>Experience with optimization tools (Gurobi, OR‑Tools, CPLEX).</li><li>Strong understanding of modern software engineering patterns and best practices.</li></ul><p><br></p>

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