דרושים » תוכנה » Data Scientist – Model Development

Requirements:
Bachelors or Masters degree in Computer Science, Mathematics, Statistics, Data Science, or related field; a PhD is an advantage.
5+ years of experience in data science roles, with at least 2 years in a team lead position.
Proven expertise in classic machine learning algorithms and techniques, including regression, classification, clustering, and feature engineering.
Extensive hands-on experience with gradient boosting frameworks such as XGBoost, LightGBM, and CatBoost.
Demonstrated success in designing, deploying, and scaling Generative AI applications (e.g., LLMs) in real-world scenarios.
Strong programming skills in Python and proficiency with data science libraries (scikit-learn, pandas, NumPy, TensorFlow, PyTorch).
Experience with cloud platforms (AWS, Azure) and MLOps tools for model deployment and monitoring in production.
Knowledge and experience in Databricks and Spark.
Excellent leadership, communication, and stakeholder management skills.
Ability to thrive in a fast-paced, collaborative, and innovative environment.
Experience in handling big data of billions of observations.

Requirements:
Bachelors or Masters degree in Computer Science, Mathematics, Statistics, Data Science, or related field; a PhD is an advantage.
5+ years of experience in data science roles.
Proven expertise in classic machine learning algorithms and techniques, including regression, classification, clustering, and feature engineering.
Extensive hands-on experience with gradient boosting frameworks such as XGBoost, LightGBM, and CatBoost.
Demonstrated success in designing, deploying, and scaling Generative AI applications (e.g., LLMs) in real-world scenarios.
Strong programming skills in Python and proficiency with data science libraries (scikit-learn, pandas, NumPy, TensorFlow, PyTorch).
Experience with cloud platforms (AWS, Azure) and MLOps tools for model deployment and monitoring in production.
Knowledge and experience in Databricks and Spark.
Ability to thrive in a fast-paced, collaborative, and innovative environment.
Experience in handling big data of billions of observations.
Preferred Skills :
Knowledge of data engineering and pipeline development.
Prior experience in fintech or the payments industry is a plus.

Requirements:
Minimum 3 years of professional experience in Data Science roles
Hands-on experience in networking and/or cybersecurity domains
Proven experience building and deploying LLM-based applications and agents (e.g., RAG pipelines, tool-use agents, prompt engineering at scale)
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 with real-time or low-latency AI inference in production environments.
Advanced degree (MSc or PhD) in Computer Science, Statistics, Mathematics, or a related quantitative field.

Requirements:
M.Sc in Computer Science, Mathematics, Statistics, Engineering or a related field
4+ years of experience in applied Data Science or Algorithmic Development, preferably in large-scale production environments.
Hands-on experience in training and fine-tuning machine learning, deep learning, and AI models
Strong programming skills in Python and proficiency in SQL.
Solid understanding of data pipelines, MLOps practices, and working with huge datasets.
Ability to mentor, collaborate, and communicate complex ideas clearly to diverse audiences.
A fast learner, problem solver, and end-to-end owner with a strong can-do approach.
Bonus Points:
Experience in the ad-tech industry or with fraud detection systems.
Familiarity with LLMs, generative AI, or representation learning for anomaly detection.
Proven track record working with large-scale distributed data systems.
Being introduced by an AppsFlyer employee

Requirements:
6+ years of experience in Data Science or Machine Learning roles.
At least 2+ years of managerial experience leading a team of 4 Data Scientists or more. .
Proven experience delivering AI/ML solutions to production in a SaaS or product environment.
Strong expertise in machine learning frameworks such as PyTorch, TensorFlow, XGBoost, or similar.
Advanced SQL skills and experience working with large datasets.
Experience working in cross-functional environments with Product and Engineering teams.
Strong communication skills in English and Hebrew.
Bachelors degree in Computer Science, Engineering, data science related degree or related fields (Masters degree is an advantage).

Requirements:
Advanced knowledge and experience in Computer Vision and Natural Language Processing, engineering aspects of developing ML and GenerativeAI models at scale.
Experience designing and executing end-to-end research and development plans and generating impact through large-scale machine learning model development. Preferably evidenced by peer-reviewed publication, patents, open sourced code or the like.
Relevant work or academic experience (MSc + 6 years of working experience, or PhD + 4 years of working experience), involved in the application of Machine Learning to business problems.
Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.).
Experience on multiple machine learning facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.).
Strong working knowledge of Python, Java, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.
Excellent English communication skills, both written and verbal.
Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels
Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators

Requirements:
* 7+ years of experience in Data Science, Applied ML, or Quantitative Analysis
* M.Sc. or PhD in Statistics, Mathematics, Computer Science, or related field
* Proven experience designing and implementing statistical and machine?learning algorithms
* Strong Python proficiency for algorithm development, modeling, and experimentation
* Strong background in time?series analysis, including forecasting and anomaly detection
* Hands?on experience with ML libraries such as scikit?learn, XGBoost, LightGBM
* Experience applying causal inference methodologies in analytical or product contexts

Requirements:
4+ years of practical analytics experience in big data environments (preferably in a B2C company).
A hands-on, passionate individual who enjoys diving deep into algorithms, data and business problems.
Excellent analytical skills with experience querying large, complex datasets.
Strong understanding of statistical methods and significance testing.
Hands-on experience with machine learning algorithms and Python.
Experience working with modern AI approaches, including applied machine learning and familiarity with generative AI tools
BSc (or higher) in Mathematics, Statistics, Engineering, Computer Science or a related quantitative field.
Self-learner, able to quickly adapt to new technologies and AI-driven workflows.
Independent, proactive problem-solver with strong ownership.
Excellent communication skills, both written and verbal.
Familiarity with the Ad-Tech industry - a big plus.
Experience implementing real-time machine learning or data-driven systems at scale - a big plus.
Experience integrating AI models into production environments or decision-making systems - a plus.
Fun to work with and a strong team player

Requirements:
Holds a M.Sc in Computer Science/Mathematics/Physics or any other relevant field - Required
Has 3+ years of experience with statistical and machine learning tools - Python, R, etc.
Strong communicative and verbal abilities to lead and guide customers through the logic of custom-built models
Has previous experience developing machine learning/ image processing/NLP or similar algorithms
Demonstrated experience utilizing probability theory and statistics
Experience with Big Data tools and cloud infrastructure; PySpark, AWS (big advantage)
Strong analytical skills; experience analyzing and processing tabular data, and extracting insights (big advantage)

Requirements:
Experience in Statistics (i.e. statistical analysis, regression analysis, ) and/or Artificial Intelligence (i.e. Data Mining, Machine Learning, ).
An appetite for Data Science applied to high-volumetry, low-latency topics.
Ability to read scientific articles, to analyze critically, and to implement as appropriate.
Good programming abilities.
True scientist skills: fast learner, curious, sense of details, rigorous.
Strong communication skills, working collaboratively with the team, able to teach concepts, and communicate clearly to a wide audience of complicated topics.
Strong problem solving skills, and deducing from specific problems wider range products.
You are very mindful about your application architecture, performance, testing and maintainability and its overall quality.
Requirements:
5+ years of hands-on experience with coding ML based solutions in high scale systems
Relevant industry experience / publications in ad-tech and recommender system.
Msc/Phd in computer science / math.
Industry experience in building engineering at scale.
Large-scale distributed systems, service oriented architecture.
Previous experience with all or some of the elements of our Stack (we mainly use Go, Python, Java, AWS, Jupyter notebooks).
Knowledge in data engineering.
Ability to transform raw data into actionable business insights.
Please submit your CV in English.