À propos
Pay Range: $65hr - $70hr
The Data Scientist will be responsible for analyzing complex datasets, building statistical and machine learning models, and delivering data-driven insights to support business decision-making. This role involves developing scalable data solutions, collaborating with cross-functional teams, and influencing strategic initiatives through advanced analytics. Responsibilities:
Perform exploratory data analysis to identify trends, patterns, and actionable insights. pply statistical techniques to analyze datasets, validate hypotheses, and support business decisions. Build, evaluate, deploy, and maintain machine learning models to address business problems. Design, execute, and analyze experiments such as A/B testing to measure the impact of product or feature changes. Develop robust, scalable, and automated data pipelines for data ingestion, processing, and transformation. Ensure data integrity, consistency, and availability for analytics and modeling workflows. Monitor the health and performance of existing data solutions, pipelines, and services. Design and implement automated monitoring and alerting for data pipelines, model performance, and system reliability. Identify, troubleshoot, and resolve data or service anomalies in a timely manner. Participate in on-call rotations to support the reliability and availability of data solutions. Create clear and effective data visualizations, dashboards, reports, and presentations for stakeholders. Collaborate with engineers, product teams, and business stakeholders to translate requirements into data-driven solutions. Provide insights and recommendations to guide short-term and long-term business strategy. Promote best practices in data science, analytics, experimentation, and model deployment. Requirement/Must Have:
Hands-on experience with data cleaning, preprocessing, exploratory data analysis, and statistical analysis. Proficiency in Python for data analysis, including experience with libraries such as pandas, NumPy, and visualization tools. Strong experience using SQL for data querying and analysis. Experience building, deploying, and maintaining data pipelines and machine learning models in production environments. Proficiency with version control systems, including Git and collaborative development workflows. Experience designing and analyzing experiments such as A/B testing. Experience:
Relevant professional experience in data science, analytics, or a related technical role. Skills:
Statistical analysis and predictive modeling. Machine learning model development and evaluation. Data pipeline design and automation. Data visualization and dashboard creation using industry-standard tools. Strong problem-solving, analytical, and critical thinking abilities. Effective communication and collaboration skills for cross-functional environments. Qualification And Education:
Bachelor's degree in Computer Science or a related technical field. Should Have:
Experience working in large-scale development or enterprise data environments. Experience with service monitoring, anomaly detection, and automated alerting for data and machine learning solutions. Strong understanding of machine learning algorithms such as regression, clustering, and decision trees. Experience building scalable and automated data pipelines. bility to communicate complex data findings clearly to technical and non-technical stakeholders.
Compétences linguistiques
- English
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