What are the responsibilities and job description for the Data Scientist (Machine Learning) position at Synectics Inc.?
Job Description
- Seeking a hands-on, data-driven Data Scientist to support the next stage of growth.
- This role will own the Machine Learning models that drive our business from development to deployment.
- Improving on sort and search models to help travelers find their perfect accommodation quickly and efficiently, refining predictive and classification models to estimate cancellations and financial outcomes, and developing new models to choose the perfect images and reviews to show to our customers.
- Your work will directly improve both customer experience and business performance.
- The ideal candidate combines top-notch model development and tuning skills with a startup mindset: pragmatic, ownership-driven, and excited to make a measurable impact.
- This is a strategic, execution-focused role for someone who can drive Machine Learning initiatives end-to-end and deliver results independently.
- Success in this role requires more than strong technical skills. Improved models and engineering must translate into better financial and customer outcomes, so strong business judgment is essential.
- Identifying the right problems to solve is just as important as the modeling itself.
- This role is positioned to have a direct and meaningful impact on the business.
- Model Development: Design, develop, and implement machine learning models to drive sort and search functions, create classification models to predict reservation cancellations, and build predictive models to support pricing strategies
- Data Analysis & Feature Engineering: Leverage your business acumen and deep understanding of travel shopping behaviors to identify, engineer, and prioritize the most impactful features that drive model performance
- Production Deployment: Collaborate with engineering teams to deploy machine learning models into production, ensuring they perform reliably, scale effectively, and maintain high-quality results
- Experimentation & A/B Testing: Design and run controlled experiments to measure and validate the effectiveness and impact of machine learning models
- Reporting & Visualization: Develop clear and insightful reports and interactive dashboards to effectively communicate model findings and performance metrics to both technical and non-technical stakeholders
- Research & Innovation: Continuously explore and apply the latest advancements in machine learning, AI, and data science to enhance our modeling capabilities and data infrastructure
- Design, develop, and optimize machine learning models for search, ranking, and recommendation systems
- Build classification models to predict user behavior such as cancellations and engagement patterns
- Develop predictive models to support pricing and revenue optimization strategies
- Analyze large datasets to identify trends, patterns, and opportunities for improvement
- Perform feature engineering to enhance model performance and accuracy
- Partner with engineering teams to deploy models into production environments
- Ensure models are scalable, reliable, and maintain consistent performance over time
- Design and execute A B testing frameworks to evaluate model effectiveness
- Build dashboards and reports to communicate insights and performance metrics
- Translate complex technical findings into clear, actionable insights for stakeholders
- Continuously research and implement new machine learning techniques to improve outcomes
- Seeking a Data Scientist with a strong focus on Machine Learning to drive the development and deployment of models that directly impact customer experience and business performance.
- This role is responsible for building, optimizing, and scaling models that support core platform functionality such as search, ranking, and predictive analytics.
- The position plays a critical role in transforming large scale data into actionable insights and intelligent systems that improve decision making and operational efficiency.
- 5 years of professional experience in a Data Scientist or Machine Learning Engineer role
- Expert-level proficiency in Python, including key machine learning libraries
- Solid understanding of statistical modeling, experimental design, and data mining techniques
- Demonstrated experience owning the full modeling lifecycle, including ETL, data cleansing, feature engineering, model development, deployment, and ongoing maintenance
- Experience with SQL and working with large datasets in a cloud environment, particularly GCP, but demonstrated expertise in other platforms can suffice
- Strong communication skills, with the ability to explain complex technical concepts to a diverse audience
- Preferred Qualifications and Prior Experience:
- Experience developing machine learning models within a GCP environment
- Familiarity with MLOps practices and tools for deployment, maintenance, and ongoing improvement of models
- Experience in the Travel or Financial Services industry
- Competitive benefits package including health coverage
- Flexible work environment
- Opportunity to work on high impact, data driven initiatives
- Career growth in a fast paced, technology focused environment
- Additional Information
- Full time position
- Hybrid work structure
- High ownership role with direct impact on business outcomes