1 to 25 of 1,488 Permanent Algorithms Jobs

Plotly Dash Qualifications: Bachelor's degree in Computer Science, Math, Engineering, or related field (Master's preferred) with 1+ years of experience Strong understanding of data structures, data modeling, algorithms, and software architecture. Proficient in probability, statistics, and algorithm development. Hands-on experience with ML and deep learning libraries (Scikit Learn, Keras, TensorFlow, PyTorch, Theano, DyLib). (Bonus) Experience with More ❯

in Computer Science, Math, Engineering, or related field (Master's preferred) with 0-5+ years of experience (depending on the level) Strong understanding of data structures, data modeling, algorithms, and software architecture. Proficient in probability, statistics, and algorithm development. Hands-on experience with ML and deep learning libraries (Scikit Learn, Keras, TensorFlow, PyTorch, Theano, DyLib). (Bonus) Experience with More ❯

complex data sets and derive actionable insights. PREFERRED EXPERIENCE: 3+ years of combined experience in machine learning model development, data analysis, and statistical modeling. Strong understanding of machine learning algorithms, model evaluation metrics, optimization techniques, and statistical analysis techniques. Demonstrated ability to implement, validate, and improve supervised and unsupervised learning models. Excellent knowledge of Excel, Python, SQL, and database systems. More ❯

of experience OR PhD with industry or research experience in relevant areas Preferred Qualifications Advanced proficiency in Python and C++ Strong knowledge of object-oriented design, data structures, and algorithms Experience in real-time or embedded software development Familiarity with network communication protocols and hardware software integration Hands-on experience with ROS, Linux-based development, and/or real-time More ❯

in Computer Science, Math, Engineering, or related field (Master's preferred) with 0-5+ years of experience (depending on the level) Strong understanding of data structures, data modeling, algorithms, and software architecture. Proficient in probability, statistics, and algorithm development. Hands-on experience with ML and deep learning libraries (Scikit Learn, Keras, TensorFlow, PyTorch, Theano, DyLib). (Bonus) Experience with More ❯

a spectrum of capital market products. Required Qualifications Bachelor's degree in computer science, Engineering, or related field, or equivalent work experience Strong background in Computer Science fundamentals including algorithms, data structures, computational complexity. Non-Technical Skills Excellent communication skills and teamwork is a must Experience collaborating efficiently within a global team. Demonstrable experience in fast-paced environments, supporting flexible More ❯

building streaming data processing and ingestion pipelines Experience building distributed data processing systems which handle a high volume of client queries Strong knowledge of object oriented programming, data structures, algorithms and design patterns Prior experience building systems used by multiple technical and non-technical teams Over 6 years' experience in Financial industry About Goldman Sachs At Goldman Sachs, we commit More ❯

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data Science is at the heart of Lyft's products More ❯

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data Science is at the heart of Lyft's products More ❯

to deploy models into production at scale. Partner with product teams to design experiments (A/B testing) and evaluate feature effectiveness. Research and implement state-of-the-art algorithms in AI/ML relevant to RegTech (e.g., anomaly detection, NLP, computer vision). Monitor, evaluate, and continuously improve models for performance, fairness, and compliance. Prepare clear documentation, dashboards, and More ❯

to deploy models into production at scale. Partner with product teams to design experiments (A/B testing) and evaluate feature effectiveness. Research and implement state-of-the-art algorithms in AI/ML relevant to RegTech (e.g., anomaly detection, NLP, computer vision). Monitor, evaluate, and continuously improve models for performance, fairness, and compliance. Prepare clear documentation, dashboards, and More ❯

to deploy models into production at scale. Partner with product teams to design experiments (A/B testing) and evaluate feature effectiveness. Research and implement state-of-the-art algorithms in AI/ML relevant to RegTech (e.g., anomaly detection, NLP, computer vision). Monitor, evaluate, and continuously improve models for performance, fairness, and compliance. Prepare clear documentation, dashboards, and More ❯

track record of delivering models to production. Proficiency in Python and ML libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow. Strong understanding of statistical modeling, machine learning algorithms, and experiment design. Solid experience with SQL and data manipulation tools (e.g., Pandas, Spark, or Dask). Experience deploying models using APIs (Flask, FastAPI), Docker, and orchestration tools (e.g., Airflow More ❯

Databricks for ML development and deployment. Hands-on experience with MLOps, CI/CD pipelines, and cloud-based deployment (AWS, Azure, or GCP). Solid understanding of data structures, algorithms, and software engineering principles. Experience working with large-scale datasets and distributed computing frameworks. Experience with deploying Retrieval-Augmented Generation (RAG) pipelines to production. Excellent analytical and problem-solving skills. More ❯

with models like LLaMA, GPT, BERT, or Grok for natural language understanding and generation, including leveraging AWS Bedrock for LLM deployment and management. Reinforcement Learning (RL): Expertise in RL algorithms (e.g., DQN, PPO, SAC) and multi-agent RL systems. Agentic AI Paradigms: Knowledge of goal-driven agents, task decomposition, and autonomous planning (e.g., ReAct, Plan- and-Execute architectures). Prompt More ❯

You combine academic rigor with practical engineering skills and exceptional client communication abilities. You will work end-to-end from project initiation through client delivery, comfortable both building sophisticated algorithms and presenting findings directly to clients. You excel at automating repetitive tasks and developing reusable frameworks that scale across multiple engagements. You should be comfortable implementing cutting-edge research while More ❯

Keras, or Scikit-learn. Familiarity with data processing tools (e.g., Pandas, NumPy). Knowledge of AI model deployment and cloud services (AWS, Google Cloud, Azure). Solid understanding of algorithms and data structures. Excellent analytical skills and problem-solving capability. Strong communication skills to work effectively with team members and stakeholders. About Us We specialize in Digital, ERP, and larger More ❯

Keras, or Scikit-learn. Familiarity with data processing tools (e.g., Pandas, NumPy). Knowledge of AI model deployment and cloud services (AWS, Google Cloud, Azure). Solid understanding of algorithms and data structures. Excellent analytical skills and problem-solving capability. Strong communication skills to work effectively with team members and stakeholders. About Us We specialize in Digital, ERP, and larger More ❯

Keras, or Scikit-learn. Familiarity with data processing tools (e.g., Pandas, NumPy). Knowledge of AI model deployment and cloud services (AWS, Google Cloud, Azure). Solid understanding of algorithms and data structures. Excellent analytical skills and problem-solving capability. Strong communication skills to work effectively with team members and stakeholders. About Us We specialize in Digital, ERP, and larger More ❯

Keras, or Scikit-learn. Familiarity with data processing tools (e.g., Pandas, NumPy). Knowledge of AI model deployment and cloud services (AWS, Google Cloud, Azure). Solid understanding of algorithms and data structures. Excellent analytical skills and problem-solving capability. Strong communication skills to work effectively with team members and stakeholders. About Us We specialize in Digital, ERP, and larger More ❯

Keras, or Scikit-learn. Familiarity with data processing tools (e.g., Pandas, NumPy). Knowledge of AI model deployment and cloud services (AWS, Google Cloud, Azure). Solid understanding of algorithms and data structures. Excellent analytical skills and problem-solving capability. Strong communication skills to work effectively with team members and stakeholders. About Us We specialize in Digital, ERP, and larger More ❯

You will work closely with data scientists, engineers, and product managers to design, implement, and deploy scalable artificial intelligence solutions. The Main Course - Responsibilities • Design and develop machine learning algorithms and models to solve complex problems and improve user experiences. • Collaborate with data engineers to build data and model pipelines. • Conduct data exploration and feature engineering to improve model accuracy More ❯

data products. We're hiring a Data Scientist to support our Sports Data Models Duties: Ideate, develop and improve machine learning and statistical models that drive Swish's core algorithms for producing state-of-the-art sports betting products. Develop contextualized feature sets using sports specific domain knowledge. Contribute to all stages of model development, from creating proof-of-concepts More ❯

structuring processes for advanced model development. Leading investigations into patterns, trends, and anomalies within complex datasets, guiding the team to uncover key insights. Designing, building, and enhancing machine learning algorithms, providing technical leadership and guidance to junior data scientists. Communicating complex findings to both technical and non-technical audiences, presenting actionable recommendations with clarity and authority. Writing and optimising complex More ❯

fundamentals in statistics and its application for building and validating ML models Understanding of Supervised, Unsupervised and Reinforcement learning approaches Strong experience in using Regression/Classification/Clustering algorithms and their application for appropriate use cases Build models using R, Python or Cloud native ML offerings from AWS, AZURE and GCP platforms Deploy ML models at scale using tools More ❯