166 Freelance Data Scientist jobs in Malaysia

Key Responsibilities:
• Partner with Data Scientists and business partners to architect, drive design, implement diagnostic & predictive analytics solutions with Python, Power BI and/or Tableau.
• Developing and maintaining advanced analytics, dashboards, and other BI solutions.
• Build custom quantitative models by applying advanced statistical methods (e.g., causal and predictive modeling, forecasting, data mining, simulation, and/or optimization)
• Interpret results of quantitative models, identify trends and issues, and develop alternatives to support business objectives.
• Perform validation and testing of models to ensure adequacy and determine need for reformulation.
• Perform software validation and/or testing requirements and activities

Education and Experience:
• Bachelor’s Degree in in Computer Science, Engineering, Mathematics, Statistics or a related field Required
• 4 + years of experience in data science, software development, tool development, database design, analytics and dashboard creation, related work Required
• Experience working in a medical device and/or regulated industry Preferred
• Experience working in/for Supply Chain and/or Quality functions Preferred

Skills and Qualification:
• Extensive experience in developing, maintaining, and managing Python, Power BI and/or Tableau driven dashboards & analytics and working knowledge of administration/architecture.
• Good exposure to Data Warehousing system like Snowflake, Teradata, or Redshift.
• Experience in documenting data flows, business processes, power point presentations
• Solid knowledge and understanding with BI, reporting, data mining, or multi-data center applications

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Responsibilities:

• Conduct exploratory data analysis (EDA) to uncover patterns, anomalies, and trends in aircraft operational and maintenance data.
• Design and maintain robust ETL pipelines that ensure data freshness, completeness, and integrity across multiple aviation data sources.
• Build end-to-end data products from development through deployment, including monitoring and ensuring system reliability in production.
• Develop and implement machine learning models (regression, classification, clustering) to predict maintenance needs and optimize operations.
• Leverage Large Language Models (LLMs) to enhance data products through automated feature extraction, data enrichment, and intelligent information retrieval and decision making.
• Create scalable data solutions that can handle real-time aircraft sensor data and maintenance logs.
• Deploy models and data pipelines to cloud infrastructure (GCP), implementing proper monitoring, alerting, and retraining workflows.
• Build intelligent automation systems that can process unstructured maintenance reports and technical documentation.
• Ensure data product reliability through robust error handling, logging, and performance optimization.
• Create clear data visualizations and communicate insights to technical teams, engineers, and management stakeholders.
• Collaborate with aviation engineers and operations teams to understand requirements and translate them into scalable analytical solutions.
• Maintain production systems including troubleshooting issues, optimizing performance, and ensuring uptime.
• Participate in code reviews and maintain comprehensive documentation for reproducibility and compliance.

Experience and Qualifications:

Required:

• BS/MS in Computer Science, Statistics, Mathematics, Engineering, or related field.
• 2-4 years of hands-on experience in data science and/or data engineering.
• Strong proficiency in Python and SQL, with experience building production-grade code. (We embrace AI-assisted coding tools to enhance productivity, but believe they work best in the hands of engineers who deeply understand code structure, debugging, and system design.)
• Solid foundation in statistics and machine learning concepts with practical implementation experience.
• Experience building and deploying data pipelines and ML models to production environments.
• Hands-on experience with cloud platforms (preferably GCP) including compute, storage, and ML services.
• Experience with software engineering practices: version control (Git), CI/CD, testing, and monitoring.
• Strong problem-solving skills with the ability to work independently on end-to-end solutions.
• Excellent communication skills to collaborate with technical and non-technical stakeholders.

Preferred:

• Experience with distributed computing and handling large-scale datasets
• Familiarity with NoSQL or Graph databases
• Experience in aviation, manufacturing, or other industrial domain
• Mandarin speaker will have an added advantage

Areas of Specialization

We work across these domains and welcome candidates with experience or strong interest in one or more of these areas:

Data Engineering for ML

• Building scalable data pipelines. (Airflow)
• Working with streaming data and real-time processing. (Dataflow, Pub/Sub)
• Model serving and API development. (FastAPI)
• Data quality and monitoring frameworks.

Machine Learning

• Classical ML algorithms and frameworks. (scikit-learn, TensorFlow, PyTorch)
• Model evaluation, feature engineering, and deployment.
• Cloud-based ML services. (especially GCP)

Modern AI & LLM Applications

• Building applications with Large Language Models.
• RAG systems and vector databases.
• Prompt engineering, auto prompt optimizers (like DSPy) and LLM evaluation.
• Experience with frameworks like Agents SDK or similar.

Operations Research

• Optimization problems in scheduling and resource allocation.
• Experience with optimization tools (OR-Tools, Gurobi).
• Applied problem-solving in operational contexts.

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go.

Join EY and help to build a better working world.

The opportunity

We are seeking a technically strong AI Modeller to design, build, and deploy advanced AI/ML models for real-world applications. You will be responsible for the full AI development lifecycle—from data preparation to model deployment—working closely with data engineers, application developers, and domain experts. This role is highly execution-focused, with minimal non-technical responsibilities.

Your key responsibilities

• Develop, train, and validate machine learning and deep learning models for various use cases.
• Preprocess and engineer features from large and complex datasets.
• Evaluate model performance using statistical and ML-specific metrics.
• Implement and optimize model training pipelines for efficiency and scalability.
• Deploy models into production environments, integrating with APIs and applications.
• Monitor and maintain model performance post-deployment, retraining as necessary.
• Stay updated with latest AI frameworks, algorithms, and tools.
• Document AI workflows, experiments, and deployment processes.

Skills and attributes for success

Ideally, you’ll also have

• Strong proficiency in Python and ML/DL libraries (TensorFlow, PyTorch, Scikit-learn).
• Solid understanding of supervised, unsupervised, and reinforcement learning techniques.
• Experience with data preprocessing, feature engineering, and model optimization.
• Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker) for production-grade deployments.
• Knowledge of distributed computing for large-scale model training.
• Ability to work with structured, semi-structured, and unstructured data.

What we look for

• Experience with NLP, computer vision, or generative AI.
• Understanding of GPU acceleration and parallel processing.
• Familiarity with cloud-based AI services (AWS AI/ML, Azure AI, Google AI Platform)

What we offer you

At EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.

Are you ready to shape your future with confidence? Apply today.

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EY | Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

Job Description - Data Scientist (Python, Problem Solving , Machine Learning) (MER0003L3Q)

Data Scientist (Python, Problem Solving , Machine Learning) Group : Mercedes-Benz Group AG

Description

About Us

At Mercedes-Benz, we don’t just build cars, we create great software. We develop tomorrow’s mobility together in our product lines, pushing the digitization of the Mercedes-Benz Group AG forward. As a tech company, we are agile, innovative, and always keep our finger on the pulse of change. This is why inner source, FOSS, secure code, DevOps, infrastructure as code (IaC), data analytics, artificial intelligence, and many more are core components of our daily work.

IT is our passion, and we move toward a bright future, sometimes quickly, sometimes creatively but always together.

We believe in integrity, trust, and transparency as part of our flexible work culture, with a strong emphasis on teamwork and the learning process, making mistakes, and achieving continuous progress together in all products we create and develop within the Mercedes-Benz Group.

Our workplace is anywhere* with a fast connection whether remotely at home, at your favorite café, or at our integrated office at Wisma Mercedes-Benz, which comes with an LRT station at its doorstep, an al fresco cafeteria, ample greenspaces, and free parking.

Task Description:

Advising the customer on the use of AI, capturing the requirement and translating the requirement into suitable mathematical models

Data preparation, exploratory data analysis and statistical analysis.

Conception of labelling processes

Selection, implementation and configuration of suitable (machine learning / semantic) models and procedures

Conception and implementation of automated pipelines for model creation and quality assurance

Conception and implementation of infrastructure and software to integrate AI into software products in a scalable way.

Ensuring compliance with applicable rules in the areas of data, AI and IT security compliance

Documentation and communication of the procedures and results in a target group-adequate form.

Responsibility and Scope for decision-making:

Independent consulting of the customer to identify new areas of application of AI.

Independent consulting of the customer on the use of AI, on capturing the requirement and translating the requirement into suitable mathematical models.

Independent data preparation, exploratory data analysis and statistical analysis, conception of labeling processes.

Independent selection, implementation and configuration of suitable (machine learning / semantic) models and procedures, also on the basis of scientific literature.

Conception and implementation of automated pipelines for model creation and quality assurance.

To integrate the design and implementation of infrastructure and software and AI into software products in a scalable manner.

Independent assurance of compliance with the relevant rules from the areas of data, AI and IT security.

Networking and sharing of knowledge and experience within the company, within the Group and beyond.

Qualifications

Qualifications / Experience:

Minimum of 5 years’ working experience in a related field is required.

Bachelor’s Degree in Computer Science, Applied Mathematics, Engineering, or any other technology related field.

Experience with Agile methodologies

Experience with Enterprise technologies

Experience with Product Oriented Teams

Programming or Data Architecture related certification

Specific knowledge/ Skill:

Analytical, passionate and drives technology and product quality

Result-oriented thinking and action

Has a broad and deep understanding of AI methods and their applicability in day-to-day operations.

Possesses broad and constantly expanded knowledge of mathematical and formal methods with their strengths and weaknesses.

Possesses broad and constantly expanded knowledge methods of data preparation, exploratory data analysis, data visualizations and statistical analysis.

Ability to implement and configure machine learning / semantic models close to the state of research.

Ability to design and implement automated pipelines for model creation and quality assurance.

Knowledge of the conception and implementation of infrastructure to integrate software and AI into software products in a scalable way.

Knowledge of applicable rules from the areas of data, AI and IT security compliance.
Ability to document and communicate the procedures and results in target group-adequate form.

Technical:

SQL/noSQL, Python or R, Spark, Apache libraries, Machine Learning algorithms, Cloud Computing and Data Architectures

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Job Summary

Our Data Scientists use their domain expertise to identify where AI can speed up operations, reduce costs, increase productivity, personalise the client experience; and build and deploy AI models. We’re looking for brilliant minds who are intellectually curious, analytical and willing to learn, with a numerate background in AI, mathematics, engineering, sciences or related disciplines.

Our Data Scientists use their domain expertise to identify where Artificial Intelligence (AI) can speed up operations, reduce costs, increase productivity and personalise client experiences. We’re looking for brilliant minds who are intellectually curious, analytical and love to learn.

About Our Digital Channels & Data Analytics (DCDA) Team

They support our corporate clients, by creating a more equitable, sustainable, and prosperous future for clients and global communities through technology, data and digital. They’re responsible for being an expert in digital products and services and partner with our sales and coverage teams.

About Corporate & Investment Banking (CIB)

For more than 170 years we’ve support clients with their transaction banking, financial markets, corporate finance and borrowing needs and provide solutions to nearly 20,000 clients in the world’s fastest-growing economies and most active trade corridors.

Key Responsibilities

Key Responsibilities

• Partner with stakeholders including our sales team, relationship managers, traders and leadership to understand where AI can optimise our business.
• Define AI business requirements with tangible, measurable and commercial success criteria.
• Mine large sets of data to uncover trends, insights, and opportunities from multiple internal and external data sources.
• Enhance data collection methods through augmentation, normalisation, and outlier removal.
• Recommend appropriate AI solutions and train AI models.
• Deliver self-service dashboards to report on business use case and success criteria.
• Use data visualisation for predicted outputs and insights and to translate complete analytics into business language.
• Embed a framework of continuous monitoring to deployed models and solutions, for continuous enhancement.
  
  

• Experience and education in AI, Mathematics, Engineering, the Sciences, or related discipline.
• Predictive models, machine learning algorithms and large language models.
• Data visualisation tools, including Matplotlib, Plotly, Power BI and Tableau.
• Natural Language Processing (NLP).
• Python programming.
• Financial mathematics.
• Time series analysis.
• Data governance and management.
• AI regulatory compliance.
• AI techniques including quantum machine learning.
  
  

• Do the right thing and are assertive, challenge one another, and live with integrity, while putting the client at the heart of what we do
• Never settle, continuously striving to improve and innovate, keeping things simple and learning from doing well, and not so well
• Are better together, we can be ourselves, be inclusive, see more good in others, and work collectively to build for the long term
  
  

• Core bank funding for retirement savings, medical and life insurance, with flexible and voluntary benefits available in some locations.
• Time-off including annual leave, parental/maternity (20 weeks), sabbatical (12 months maximum) and volunteering leave (3 days), along with minimum global standards for annual and public holiday, which is combined to 30 days minimum.
• Flexible working options based around home and office locations, with flexible working patterns.
• Proactive wellbeing support through Unmind, a market-leading digital wellbeing platform, development courses for resilience and other human skills, global Employee Assistance Programme, sick leave, mental health first-aiders and all sorts of self-help toolkits
• A continuous learning culture to support your growth, with opportunities to reskill and upskill and access to physical, virtual and digital learning.
• Being part of an inclusive and values driven organisation, one that embraces and celebrates our unique diversity, across our teams, business functions and geographies - everyone feels respected and can realise their full potential.

• Seniority level Entry level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Banking

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Company Description

At Western Digital, our vision is to power global innovation and push the boundaries of technology to make what you thought was once impossible, possible.

At our core, Western Digital is a company of problem solvers. People achieve extraordinary things given the right technology. For decades, we’ve been doing just that—our technology helped people put a man on the moon and capture the first-ever picture of a black hole.

We offer an expansive portfolio of technologies, HDDs, and platforms for business, creative professionals, and consumers alike under our Western Digital, WD, WD_BLACK, and SanDisk Professional brands.

We are a key partner to some of the largest and highest-growth organizations in the world. From enabling systems to make cities safer and more connected, to powering the data centers behind many of the world’s biggest companies and hyperscale cloud providers, to meeting the massive and ever-growing data storage needs of the AI era, Western Digital is fueling a brighter, smarter future.

Today’s exceptional challenges require your unique skills. Together, we can build the future of data storage.

Responsibilities

• Work with data scientists, data engineers, software engineers, process & product engineers, design engineers, etc collaboratively to develop new data science solutions that improve productivity and operations metrics.
• Researching and developing scalable Generative-AI solutions using AWS Bedrock platform, Large Language Models (LLM) and prompt engineering for factory/engineering usage
• Deploy models and solutions using DevOps/MLOps tools such as Docker, Kubernetes, MLflow, AWS & Edge to ensure scalability and reproducibility.
• Collaborate in cross-functional teams to integrate AI/ML algorithms, image analytics and software into the Analytics systems (including chatbot/AR/Computer Vision) as well as develop prototypes.
• Design, develop, deploy and maintain Analytics Systems/solutions (Data engineering, Data Science, Chatbot, AI, Generative-AI, AR, Computer vision and Visualization/Web App) independently and delivered on time.
• Meeting users, gathering user requirements and communicating requirements to a technical team member for technical solution design, feasibility study & planning.
• Translate User Request into Analytics Solution from a system perspective. Prepare and deliver presentations with data visualizations and business conclusions.
• Constantly learn new front tier technology and creatively apply/deliver solutions to manufacturing operations to meet KPIs.

Qualification

• Masters or Bachelor Degree in Computer science, data science, computer engineering, information technology, or relevant work experience and education background.
• We will also consider applicants with the equivalent combination of education, technical expertise, training, or work experience.
• Preferably minimum 3-4years of working experience in related field (Generative-AI & Chatbot).

Skills

• Required: Python, LLM, Prompt Engineering, Chatbot, Generative -AI, Augmented Reality, Computer Vision
• Added Advantage: Agentic AI and Multi-Agent architecture.
• Practical experience in application of ML and Deep Learning algorithms.

• SQL, Relational databases, Big Data platforms, AWS Redshift, PRESTO, ETL, SSIS etc.
• Some experience with web front end development: .NET, VB.NET, C#, HTML/CSS, JavaScript, NodeJS, JQuery & Angular
• Ability to learn quickly and become productive on new technologies, APIs, development languages and frameworks.
• Experience in data mining, data wrangling, and handling JSON, CSV files.
• Hands on experience with Docker, Kubernetes, Edge computing and AWS. etc
• Experience with data visualization methods (Spotfire, PowerBI, Grafana)
• The ability to problem solves and provide complex solutions with minimal supervision
• Knowledge of Agile development, SCRUM and Application Lifecycle Management
• Excellent communications and presentation skills, with the ability to synthesize, simplify and explain complex problems to different types of audience, including executives. A great team player.
• Self-motivated, strong ownership and ability to work independently with minimal supervision

Western Digital thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.

Western Digital is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Notice To Candidates: Please be aware that Western Digital and its subsidiaries will never request payment as a condition for applying for a position or receiving an offer of employment. Should you encounter any such requests, please report it immediately toWestern Digital Ethics Helpline or email .

Join to apply for the Data Scientist role at Epergne Solutions .

Development experience in one or more object-oriented programming languages (e.g., Python, Java).

Experience working closely with data scientists, data engineers, software engineers, data managers, and business partners.

Ability to build scalable, reusable, impactful data science products, often containing statistical or machine learning algorithms, in collaboration with data and software engineers.

Proficiency in conducting data analyses to generate actionable business insights.

Hands-on experience (typically 5+ years) designing, planning, prototyping, productionizing, maintaining, and documenting reliable and scalable data science products in complex environments.

Applied knowledge of data science tools and approaches across all stages of the data lifecycle.

Thorough understanding of the mathematical foundations of statistics and machine learning.

Development experience in object-oriented programming languages (e.g., Python, Java).

Strong software engineering and machine learning system design experience.

Advanced SQL knowledge.

Customer-centric and pragmatic mindset, focusing on value delivery and swift execution while maintaining attention to detail.

Excellent communication skills, including written communication.

• Mid-Senior level

• Full-time

• Engineering and Information Technology

• IT Services and IT Consulting

About Us

At Mercedes-Benz, we don’t just build cars, we create great software. We develop tomorrow’s mobility together in our product lines, pushing the digitization of the Mercedes-Benz Group AG forward. As a tech company, we are agile, innovative, and always keep our finger on the pulse of change. This is why inner source, FOSS, secure code, DevOps, infrastructure as code (IaC), data analytics, artificial intelligence, and many more are core components of our daily work.

IT is our passion, and we move toward a bright future, sometimes quickly, sometimes creatively but always together.

We believe in integrity, trust, and transparency as part of our flexible work culture, with a strong emphasis on teamwork and the learning process, making mistakes, and achieving continuous progress together in all products we create and develop within the Mercedes-Benz Group.

Our workplace is anywhere* with a fast connection whether remotely at home, at your favorite café, or at our integrated office at Wisma Mercedes-Benz, which comes with an LRT station at its doorstep, an al fresco cafeteria, ample greenspaces, and free parking.

Task Description:

• Advising the customer on the use of AI, capturing the requirement and translating the requirement into suitable mathematical models
• Data preparation, exploratory data analysis and statistical analysis.
• Conception of labelling processes
• Selection, implementation and configuration of suitable (machine learning / semantic) models and procedures
• Conception and implementation of automated pipelines for model creation and quality assurance
• Conception and implementation of infrastructure and software to integrate AI into software products in a scalable way.
• Ensuring compliance with applicable rules in the areas of data, AI and IT security compliance
• Documentation and communication of the procedures and results in a target group-adequate form.

Responsibility and Scope for decision-making:

• Independent consulting of the customer to identify new areas of application of AI.
• Independent consulting of the customer on the use of AI, on capturing the requirement and translating the requirement into suitable mathematical models.
• Independent data preparation, exploratory data analysis and statistical analysis, conception of labeling processes.
• Independent selection, implementation and configuration of suitable (machine learning / semantic) models and procedures, also on the basis of scientific literature.
• Conception and implementation of automated pipelines for model creation and quality assurance.
• To integrate the design and implementation of infrastructure and software and AI into software products in a scalable manner.
• Independent assurance of compliance with the relevant rules from the areas of data, AI and IT security.
• Networking and sharing of knowledge and experience within the company, within the Group and beyond.

Qualifications / Experience:

• Minimum of 5 years’ working experience in a related field is required.
• Bachelor’s Degree in Computer Science, Applied Mathematics, Engineering, or any other technology related field.
• Experience with Agile methodologies
• Experience with Enterprise technologies
• Experience with Product Oriented Teams
• Programming or Data Architecture related certification

Specific knowledge/ Skill:

• Excellent communication skills
• Good customer service orientation
• Analytical, passionate and drives technology and product quality
• Result-oriented thinking and action
• Has a broad and deep understanding of AI methods and their applicability in day-to-day operations.
• Possesses broad and constantly expanded knowledge of mathematical and formal methods with their strengths and weaknesses.
• Possesses broad and constantly expanded knowledge methods of data preparation, exploratory data analysis, data visualizations and statistical analysis.
• Ability to implement and configure machine learning / semantic models close to the state of research.
• Ability to design and implement automated pipelines for model creation and quality assurance.
• Knowledge of the conception and implementation of infrastructure to integrate software and AI into software products in a scalable way.
• Knowledge of applicable rules from the areas of data, AI and IT security compliance.
• Ability to document and communicate the procedures and results in target group-adequate form.

Job Description - Data Scientist (MER0003L3Q)

Description

Task Description:

1. Advising the customer on the use of AI, capturing the requirement and translating the requirement into suitable mathematical models.
2. Data preparation, exploratory data analysis and statistical analysis. Conception of labelling processes.
3. Selection, implementation and configuration of suitable (machine learning / semantic) models and procedures.
4. Conception and implementation of automated pipelines for model creation and quality assurance.
5. Conception and implementation of infrastructure and software to integrate AI into software products in a scalable way.
6. Ensuring compliance with applicable rules in the areas of data, AI and IT security compliance.
7. Documentation and communication of the procedures and results in a target group-adequate form.

Responsibility and Scope for decision-making:

1. Independent consulting of the customer to identify new areas of application of AI.
2. Independent consulting of the customer on the use of AI, on capturing the requirement and translating the requirement into suitable mathematical models.
3. Independent data preparation, exploratory data analysis and statistical analysis, conception of labeling processes.
4. Independent selection, implementation and configuration of suitable (machine learning / semantic) models and procedures, also on the basis of scientific literature.
5. Conception and implementation of automated pipelines for model creation and quality assurance.
6. To integrate the design and implementation of infrastructure and software and AI into software products in a scalable manner.
7. Independent assurance of compliance with the relevant rules from the areas of data, AI and IT security.
8. Networking and sharing of knowledge and experience within the company, within the Group and beyond.

Qualifications

Qualifications / Experience:

1. Bachelor’s Degree in Computer Science, Applied Mathematics, Engineering, or any other technology related field.
2. Experience with Agile methodologies.
3. Experience with Enterprise technologies.
4. Experience with Product Oriented Teams.
5. Programming or Data Architecture related certification.

Specific knowledge/ Skill:

1. Excellent communication skills.
2. Good customer service orientation.
3. Analytical, passionate and drives technology and product quality.
4. Result-oriented thinking and action.
5. Has a broad and deep understanding of AI methods and their applicability in day-to-day operations.
6. Possesses broad and constantly expanded knowledge of mathematical and formal methods with their strengths and weaknesses.
7. Possesses broad and constantly expanded knowledge methods of data preparation, exploratory data analysis, data visualizations and statistical analysis.
8. Ability to implement and configure machine learning / semantic models close to the state of research.
9. Ability to design and implement automated pipelines for model creation and quality assurance.
10. Knowledge of the conception and implementation of infrastructure to integrate software and AI into software products in a scalable way.
11. Knowledge of applicable rules from the areas of data, AI and IT security compliance.
12. Ability to document and communicate the procedures and results in target group-adequate form.

Technical:

1. SQL/noSQL, Python or R, Spark, Apache libraries, Machine Learning algorithms, Cloud Computing and Data Architectures.