Position ObjectiveDesign, develop, and implement advanced analytical models, machine learning algorithms, and AI-driven solutions to transform large volumes of data into strategic insights, improve decision-making, optimize business processes, and generate measurable business value.Key ResponsibilitiesAnalyze large structured and unstructured datasets to identify patterns, trends, risks, and opportunities.Design, train, validate, and deploy predictive, prescriptive, and machine learning models.Develop advanced analytics and artificial intelligence solutions aligned with business objectives.Translate business problems into analytical frameworks and data-driven solutions.Define metrics, methodologies, and experiments to evaluate model performance and business impact.Collaborate with business, technology, data engineering, and product teams to implement scalable solutions.Build and optimize data pipelines and model deployment workflows.Ensure data quality, consistency, and reliability for analytical initiatives.Education RequirementsBachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Physics, Economics, Actuarial Science, or a related field.Master's degree or PhD in Data Science, Artificial Intelligence, Machine Learning, Statistics, Operations Research, or a related discipline is preferred.Required Experience~5 to 8+ years of experience in data science, advanced analytics, machine learning, or related roles.
~ Proven experience developing and deploying machine learning models in production environments.
~ Experience working with large-scale datasets and cloud-based data platforms.
~ Experience leading high-impact analytics or AI projects.
~ Strong experience working with business stakeholders and executive audiences.Technical SkillsAdvanced proficiency in PythonStrong knowledge of libraries and frameworks such as:PandasNumPyScikit-learnTensorFlowPyTorchXGBoostLightGBMAdvanced SQL skills.Experience with relational and non-relational databases.Experience with cloud platforms such as:AWSGoogle Cloud PlatformMicrosoft AzureKnowledge of distributed processing tools such as:SparkDatabricksHadoopExperience with MLOps practices, including:Model versioningModel monitoringPipeline automationModel deploymentStrong understanding of statistics, probability, optimization, and mathematical modeling.Experience with data visualization tools such as Power BI, Tableau, Looker, or similar platforms.
Sign in
To continue your applicationor continue with email
By continuing you agree to our Terms & Privacy Policy.
