Requirements:
MSc in Computer Science/Engineering or related field with a focus on applied statistics, AI, machine learning, or related fields - a must.
6+ years of production environment experience, working with predictive and probabilistic models, clustering algorithms, classification models, search and recommendation techniques - a must.
Proven record for successful production implementation of translating product/business requirements into a technical solution.
Team player, Ability to handle several tasks simultaneously.
Strong knowledge in Python, SQL, and NoSQL.
Spark and Big data technologies experience an advantage.
Research experience - an advantage.
Experience with e-commerce - an advantage.

Requirements:
5 + years of hands-on experience developing and deploying machine-learning or data-science solutions with Python and SQL.
Proven, end-to-end experience building AI- and machine learning-based solutions from prototype to production deployment.
Demonstrated success shipping data-intensive services to production on cloud infrastructure (AWS preferred) using data tools such as PostgreSQL, Databricks, Spark, or Airflow.
Deep understanding of machine-learning fundamentals and practical expertise with frameworks such as TensorFlow, PyTorch, or scikit-learn.
Expertise in machine learning metrics and quality control.
Solid understanding of software-engineering best practices (including design patterns, data structures, and version control).
Excellent interpersonal and communication skills, with the ability to explain complex technical concepts to non-technical stakeholders and collaborate across teams.
Its even better if you have:
Experience with Agile development in fast-paced, delivery-driven environments.
Familiarity with CI/CD practices, containers, Kubernetes, and serverless or microservice architectures.
Experience with geospatial analysis, government data, survey research, or civic-tech applications.
A track record of contributing to open-source projects.
A college or graduate degree in a relevant field.

Requirements:
MSc in Computer Science/Engineering or related field with a focus on applied statistics, AI, machine learning, or related fields - a must.
6+ years of production environment experience, working with predictive and probabilistic models, clustering algorithms, classification models, search and recommendation techniques - a must.
Proven record for successful production implementation of translating product/business requirements into a technical solution.
Team player, Ability to handle several tasks simultaneously.
Strong knowledge in Python, SQL, and NoSQL.
Spark and Big data technologies experience an advantage.
Research experience - an advantage.
Experience with e-commerce - an advantage.

Requirements:
Minimum 3 years of professional experience in Data Science roles
Hands-on experience in networking and/or cybersecurity domains
Strong foundation in classical machine learning methods (supervised, unsupervised learning, clustering)
Practical experience with deep learning frameworks such as TensorFlow or PyTorch, including NLP techniques
Proven experience deploying models on cloud platforms like AWS, Azure, or Google Cloud
Excellent analytical, problem-solving, and communication skills
Self-motivated, collaborative, and able to work independently
How to Stand Out
Experience building agentic systems using Retrieval-Augmented Generation (RAG), including tool orchestration, benchmarking frameworks, and vector databases (e.g., FAISS, Pinecone)
Prior experience working in a fast-paced, high-growth environment
Advanced degree (MSc or PhD) in Computer Science, Statistics, Mathematics, or a related quantitative field.

Requirements:
2 + years as a leader of engineering or data science teams, with a track record of shipping data-intensive tools or services to production.
6 + years hands‑on building data-driven solutions with Python and SQL.
Experience deploying services using cloud-based infrastructure and data tools such as PostgreSQL, Databricks, and Spark.
Strong understanding of the key concepts and usage of modern AI tools such as LLMs, RAG systems, and AI agents.
Solid software engineering fundamentals (including design patterns, data structures, and version control) and familiarity with Agile practices.
Proven ability to manage project scope, timelines, and cross‑team dependencies.
Comfort implementing rapid, iterative development processes while also prioritizing quality, reliability, and maintainability.
Excellent command of English, both verbal and written, and comfortable presenting technical topics to non‑technical stakeholders.
Its even better if you have:
Proficiency with CI/CD tools and practices, containers, serverless architectures, and automated testing and monitoring.
Experience deploying models to production using leading machine learning frameworks such as TensorFlow or PyTorch.
Experience with Agile development processes and project management in JIRA.
Expertise in machine learning metrics and monitoring.
Experience with geospatial analysis, government data, survey research, or civic tech applications.
Demonstrated success hiring and developing technical talent.
Contributions to open‑source projects or an advanced degree in a relevant field.

Requirements:
MSc in Computer Science, Engineering, or a related field
Focus on AI, ML, or DS.
5+ years of experience in DS roles, with a strong emphasis on building and deploying machine learning models in production environments.
Expertise in Python and SQL.
Experience with machine learning frameworks such as TensorFlow or PyTorch.
Familiarity with cloud platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker, Kubernetes).
Proven experience in developing, fine-tuning, and deploying ML models, particularly in NLP.
Ability to translate complex business problems into data-driven solutions.
Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Requirements:
* MSc in Computer Science, Engineering, or a related field
* Focus on AI, ML, or DS.
* 5+ years of experience in DS roles, with a strong emphasis on building and deploying machine learning models in production environments.
* Expertise in Python and SQL.
* Experience with machine learning frameworks such as TensorFlow or PyTorch.
* Familiarity with cloud platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker, Kubernetes).
* Proven experience in developing, fine-tuning, and deploying ML models, particularly in NLP.
* Ability to translate complex business problems into data-driven solutions.
* Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders. Preferred Qualifications:
* Background in academic or industrial research in AI.
* Familiarity with the e-commerce domain and related data challenges.
* Previous experience leading projects in a DS capacity.

Requirements:
5+ years experience as a Data Scientist
2+ years experience working with Deep Learning.
Experience working with recommender systems - an advantage
Hands-on experience building and deploying deep learning models to production
High level scripting and programming skills in Python
Superior verbal, visual, and written communication skills to educate and work with cross functional teams on controlled experiments.
Team player, responsible, delivery-oriented
Troubleshooter, problem-solver who knows how to navigate trade-offs
Work experience as a data analyst - an advantage
At least a Master's degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field.
Experience in ML over user personalization, ad-tech, or highly imbalanced data- an advantage.

Requirements:
Proven strong expertise (8+ years) as a data scientist and machine-learning researcher.
Proven strong expertise (8+ years) in Python, with a production-level design and coding skills and hands-on experience with coding machine learning / statistical modeling based solutions
M.Sc. in Computer Science, Mathematics, Engineering or a related field, with strong theoretical background in supervised & unsupervised modeling and various other statistical modeling techniques
High-level experience with databases approaches, such as SQL and document-oriented (e.g. MongoDB) and big data
Experience in data analysis and visualization
Strong problem solving and critical thinking skills
Can-do approach
Background in Cybersecurity - an advantage
Theoretical and practical background in Generative AI - an advantage

Requirements:
What Experience Will Drive to Success:
* Bachelors degree in data Science, Computer Science, Computer Engineering, or related field.
* 2+ years of experience in AI/ML engineering, with a proven track record of building and deploying ML & AI systems.
* Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
* Hands-on experience with Big Data processing frameworks (Apache Spark, Dask, Ray).
* Hands-on experience with LLMs and AI Frameworks (LangChain, OpenAI, HuggingFace, LangGraph, etc.)
* Experience with Git and Jenkins.
* Strong problem-solving skills, a passion for innovation, and a self-driven mindset.
* Excellent communication and collaboration skills.
* Familiarity with AWS AI/ML services and cloud-based deployments (Advantage).
* Experience working with MLOps tools, including model registry, experiment tracking, and model serving (Advantage).
What We Are Looking For Independent and Self-Driven: Were building an AI Department from the ground up, so we need someone who is proactive, takes ownership, and thrives in a startup-like environment. Passion for Innovation: Whether its building scalable data infrastructure or creating advanced AI models, we are looking for someone passionate about solving complex challenges and delivering innovative solutions. Collaboration Skills: Appdome is all about teamwork. You will collaborate with engineers, data scientists, and product teams to build impactful solutions. Strong communication and interpersonal skills are key. Adaptability and Problem-Solving: Things move quickly at Appdome. You should be able to adapt to changing requirements and quickly solve problems in a fast-paced, dynamic environment. Can-Do Attitude: Were looking for motivated individuals who take the initiative, face challenges head-on, and can work independently while contributing to team success. About the Company: Appdome's mission is to protect every mobile app worldwide and its users. We provide mobile brands with the only patented, centralized, data -driven Mobile Cyber Defense Automation platform. Our platform delivers rapid no-code, no-SDK mobile app security, anti-fraud, anti-malware, anti-cheat, anti-bot implementations, configuration as code ease, Threat-Events threat-aware UI / UX control, ThreatScope Mobile XDR, and Certified Secure DevSecOps Certification in one integrated system. With Appdome, mobile Developers, cyber and fraud teams can accelerate delivery, guarantee compliance, and leverage automation to build, TEST, release, and monitor the full range of cyber, anti-fraud, and other defenses needed in mobile apps from within mobile DevOps and CI/CD pipelines.