Job Summary:

• Integrate and process data for Data Science projects
• Create and optimize statistical models and AI / ML algorithms
• Conduct talks with clients and field specialists in order to clarify expectations from the results of data analysis
• Cooperate with a team, data analysts and engineers, business analysts and architects of Data Science solutions
• Analyzes and understands a large variety of data
• Drives learnings, generates hypotheses and identifies optimization potentials
• Uses and develops machine learning technologies
• Transfers and maintains developed solutions in a productive environment
• Identifies and integrates new data sources

Skills on Resume:

• Data Integration (Hard Skills)
• Statistical Modeling (Hard Skills)
• Client Communication (Soft Skills)
• Team Collaboration (Soft Skills)
• Data Analysis (Hard Skills)
• Hypothesis Generation (Hard Skills)
• Machine Learning Development (Hard Skills)
• Solution Deployment (Hard Skills)

Job Summary:

• Able to configure and operate data science/machine learning operations toolchains with cloud-native analytic solutions
• Comfortable delivering secure-by-design implementations
• Coaching in the use of data science techniques and software to solve business problems
• Lead others on a project, delegating tasks and setting/managing delivery to deadlines
• Build and coordinate scalable data systems
• Ensuring that the systems fit the business requirements
• Solving problem analysis and develop data modeling, involving mining and production processes
• Improve data reliability, efficiency and quality
• Build models, algorithms, prototypes and proofs of concept.

Skills on Resume:

• Cloud-Native Solutions (Hard Skills)
• Secure Implementations (Hard Skills)
• Data Science Coaching (Soft Skills)
• Project Leadership (Soft Skills)
• Scalable Data Systems (Hard Skills)
• Business Requirements Alignment (Hard Skills)
• Problem Analysis (Hard Skills)
• Model Development (Hard Skills)

Job Summary:

• Improve factory and production process with concept of Digital Factory, Intelligent Manufacturing, Modeling, IoT and AI.
• Analyze existing in-process data from manufacturing equipment, Test process and IoT device to get insight into improvement opportunities and root-cause analysis.
• Apply machine learning technology in prediction and analysis of process data, time series, images, texts to empower production process.
• Develop live analysis dashboards for monitoring and analyzing data from manufacturing, testing process and equipment performance.
• Design and maintain well-structured rational database schemas.
• Create automated ETL pipelines for IoT device
• Research technology and trending in Industry 4.0, IoT application, simulation, and modeling in manufacturing etc.
• Educate others on scientific investigation.

Skills on Resume:

• Digital Manufacturing (Hard Skills)
• Data Analysis (Hard Skills)
• Machine Learning (Hard Skills)
• Dashboard Development (Hard Skills)
• Database Design (Hard Skills)
• ETL Automation (Hard Skills)
• Industry Research (Hard Skills)
• Training Others (Soft Skills)

Job Summary:

• Working individually and in small teams
• Collaborate with data scientists to create scalable ML solutions for business problems at a local and global level
• Work closely with Data Scientists teams, Software Engineering teams, and Process Engineering teams to drive model implementations and new algorithms
• Attending morning and evening meetings to align with sites across the globe
• Gather and transform data to make it useable for analytics, including Deep-learning/Machine-learning
• Use ML tools such as annotating data. 
• Work with other Data Scientists on designing AI workflow and end-to-end pipelines.
• Develop, Test, Optimize and Deploy Deep-learning/Machine-learning models on-prem and cloud platforms (GCP, AWS, and Azure)
• Improve, Expand and Maintain Deep-learning/Machine-learning models
• Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and TPUs/GPUs)
• Design visualization modes for intermediate and final results.

Skills on Resume:

• ML Solutions Development (Hard Skills)
• Team Collaboration (Soft Skills)
• Algorithm Implementation (Hard Skills)
• Global Meeting Coordination (Soft Skills)
• Data Transformation (Hard Skills)
• AI Workflow Design (Hard Skills)
• Model Deployment (Hard Skills)
• Visualization Design (Hard Skills)

Job Summary:

• Work closely with the business and technical project manager to understand the business requirement and translate into technical specs.
• Provide analysis reports and estimations.
• Design, develop, install, test and maintain data integrations from a variety of formats including files, database extracts and external APIs into data stores (including Snowflake, Elastic, S3, etc) using ETL tools, techniques and programming languages like Python, Spark, SQL, etc.
• Build high-performance data engineering algorithms and prototypes.
• Create flexible data models, tune queries and ETL components.
• Manage job orchestration using tools like Airflow.
• Research possible customization for tuning, cost optimization, performance enhancements, data reliability and quality.
• Ensure that all solutions meet the business/company requirements for solution data reliability, quality and disaster recovery.
• Own the application/data end-to-end from requirements to post production working closely with other teams. 
• Provide engineering leadership by actively advocating best practices and standards for software engineering.
• Collaborate with other team members such as data architects, data scientists etc.
• Consistently contribute to the project management practices using Agile method.
• Present the prototype to the stakeholders and leadership.

Skills on Resume:

• Technical Specification (Hard Skills)
• Data Integration (Hard Skills)
• ETL Development (Hard Skills)
• Algorithm Prototyping (Hard Skills)
• Data Modeling (Hard Skills)
• Job Orchestration (Hard Skills)
• Performance Tuning (Hard Skills)
• Agile Project Management (Soft Skills)

Job Summary:

• Help develop and build a robust data and analytics infrastructure which expose data via relevant interfaces to clients and other teams
• Work with senior team members to deploy and test applications at scale
• Work with cross-functional business, analytics, and IT teams to deliver simple, secure and multi-faceted use cases
• Construct reliable and fault tolerant data pipeline workflows
• Use best practices in continuous integration and delivery
• Working with multiple data sources, including On-prem and cloud(AZUR, GCP, AWS, etc)
• Apply Computer Vision Tools to images to help extract key feature
• Apply advanced analytics on time series data to help extract key features
• Work with sensors and edge-nodes to collect and analyze Fab data

Skills on Resume:

• Infrastructure Development (Hard Skills)
• Application Scaling (Hard Skills)
• Cross-Functional Delivery (Soft Skills)
• Pipeline Construction (Hard Skills)
• Continuous Integration (Hard Skills)
• Cloud Data Management (Hard Skills)
• Computer Vision Application (Hard Skills)
• Time Series Analysis (Hard Skills)

Job Summary:

• Leading a team of technical consultants
• Gathering new requirements from multiple countries (global blueprint/adapting the template)
• Involved in root cause analysis on technical issues
• Build and maintain data ETL jobs using a range of tools including PostgreSQL, Java and Kafka
• Integrating, consolidating and transmitting data while maintain Atom’s high data quality standards
• Liaise with senior stakeholders to gain an understanding of their requirements whilst possessing the ability to translate these business requirements into technical delivery
• Design and integrity of data solutions delivered to the business
• Understand and implement Atom’s vision, strategy and principles for data management
• Analyze data and build data analysis tools
• Discover new perspectives for old data and deep-dive failure analysis
• Produce / Present meaningful data visualization to higher-ups and across various involved teams

Skills on Resume:

• Team Leadership (Soft Skills)
• Global Requirements Analysis (Soft Skills)
• Root Cause Analysis (Hard Skills)
• ETL Maintenance (Hard Skills)
• Data Integration (Hard Skills)
• Stakeholder Liaison (Soft Skills)
• Data Solution Design (Hard Skills)
• Data Visualization (Hard Skills)