Data Science & Machine Learning Jobs

Position Summary: The role will lead and mentor a team of data scientists and analysts responsible for delivering machine learning, artificial intelligence, and advanced analytics projects.. Minimum 5 years of experience in data science, machine learning, statistical modeling, or optimization in an industry or research setting.. Experience with big data technologies such as Hadoop, Spark, and cloud platforms (AWS, GCP, Azure) is a plus.. Familiarity with machine learning frameworks, such as TensorFlow, PyTorch, or scikit-learn.. Advanced proficiency in Python, SQL, PySpark, or similar analytic tools.

Design, develop, and deploy AI models and algorithms for various applications, including predictive analytics, automation, natural language processing, computer vision, and deep learning.. Proven experience in AI, machine learning, and deep learning development.. Proficiency in AI and machine learning frameworks such as TensorFlow, Keras, PyTorch, or Scikit-learn.. Familiarity with cloud platforms (AWS, Azure, Google Cloud) and deploying machine learning models in production environments. Experience with natural language processing (NLP) or computer vision.

We are seeking a highly skilled Applied Machine Learning Engineer for an exciting on-site contract opportunity with a leading global technology company. This position is offered through a premier IT consulting firm and provides the chance to work on cutting-edge machine learning projects in a fast-paced, innovative environment. Develop and optimize classification methods, deep learning models, and predictive algorithms for real-world applications. 6+ years of experience in applied machine learning, deep learning, and predictive modeling. Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

We are seeking an experienced Senior Data Scientist with over 5 years of experience in Data Science, Machine Learning (ML), and Artificial Intelligence (AI) to join our team in Redwood City, SF Bay Area. Ensure best practices in ML model validation, interpretability, and performance optimization. Work with big data technologies and cloud platforms such as AWS, GCP, or Azure to scale AI/ML solutions. Deep expertise in machine learning algorithms, deep learning, NLP, computer vision, and reinforcement learning. Hands-on experience with cloud platforms (AWS, GCP, Azure) and big data technologies (Spark, Hadoop, Snowflake).

A leading proprietary trading firm specializing in quantitative and algorithmic trading across global financial markets is seeking a Software Engineer - AI & Machine Learning to enhance their trading systems and develop state-of-the-art AI-driven models. Collaborate with quant researchers and traders to refine trading strategies using AI insights. or Java. Strong experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn). Machine Learning Expertise: Hands-on experience in deep learning, reinforcement learning, time-series forecasting, and NLP. Big Data & Infrastructure: Experience with distributed computing (Spark, Ray), cloud platforms (AWS, GCP), and database management (SQL, NoSQL).

The Fay Group originated in 2008, is a full-scale real estate services company that offers mortgage servicing, property renovations, business purpose lending, insurance, and more to homeowners, investors, and clients nationwide.. Reporting to the SVP, Data Science, this position supports the data science team in developing and implementing statistical models that use machine learning, time-series analysis, Monte-Carlo simulations, and reinforcement learning techniques.. This role is responsible for data mining, predictive modeling, and statistical analysis to help solve complex business problems and improve operational efficiencies.. Strong working knowledge of relevant programming languages, tools, and technologies (e.g., Python, R, Hadoop, Spark, etc.. Equity and Inclusion are embedded into our way of working at Fay. We believe that the best ideas come from having a team that is diverse in backgrounds, experiences, and perspectives.

Develop state-of-the-art machine learning models to solve real-world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems.. Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods.. Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas).. Strong publication record in Natural Language Processing, Machine Learning, Deep Learning or Reinforcement Learning at major conferences or journals.. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

Programs Machine Learning frameworks using Python and R. Develops and models software solutions using Natural Language Processing (NLP), Information Retrieval, Machine Comprehension, Question Answering/Conversational Artificial Intelligence (AI), Reinforcement Learning, Knowledge Graph, Causal Inference, and Design of Experiment.. Conducts exploratory data analysis according to measurements, unstructured data analysis, predictive analytics, and prescriptive analytics using Big Data, NLP, and chatbot technologies (Elasticsearch and Solr).. Education and Experience: Bachelor’s degree (or foreign education equivalent) in Computer Science, Data Science, Analytics, Operations Research, Engineering, Information Technology, Information Systems, Statistics, Mathematical Finance, or closely related field and five (5) years of experience as a Senior Manager, Data Science (or closely related occupation) building Artificial Intelligence/Machine Learning (AI/ML) models in a financial services environment.. Or, alternatively, Master’s degree (or foreign education equivalent) in Computer Science, Data Science, Analytics, Operations Research, Engineering, Information Technology, Information Systems, Statistics, Mathematical Finance, or closely related field and three (3) years of experience as a Senior Manager, Data Science (or closely related occupation) building Artificial Intelligence/Machine Learning (AI/ML) models in a financial services environment.. using classical NLP and ML methods (Deep Learning (DL) and embeddings).

This may involve data exploration, high-performance data processing, and machine learning algorithm exploration.. This may involve speeding up training, making a data processing easier, or data management tooling.. Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark).. Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).. Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.

Role - Researcher AI & Machine Learning - AI & Data Consultant. Communicate complex research results to both technical and non-technical stakeholders. Expertise in machine learning libraries (e.g., TensorFlow, PyTorch, Keras, Scikit-learn). Experience in cloud platforms (e.g., AWS, Azure, Google Cloud) for model deployment. Experience with deep learning, natural language processing (NLP), computer vision, or reinforcement learning

Command of the foundational scientific python ecosystem (pytorch/jax/tensorflow, numpy, scipy, pandas, scikit-learn). PhD in computer science, data science, artificial intelligence, or related field. 3+ years of combined Python engineering and machine learning experience with a focus on Deep Learning. Experience participating in a top conference in High Performance Computing, Deep Learning, Machine Learning or AI domains. Experience with deep learning libraries and frameworks (TensorFlow, JAX, PyTorch, Langchain, etc.)

Contributes to developing and refining data governance and data quality standards across the organization. Proficiency in Python, R, and SQL for data manipulation, analysis, and modeling. Familiarity with machine learning libraries (e.g., Scikit-learn, TensorFlow) and data visualization tools (e.g., Tableau, Power BI). Experience with cloud platforms (e.g., AWS, Azure), Kubernetes and big data tools (e.g., Hadoop, Spark). Knowledge of deep learning, NLP, or other specialized data science domains.

As a Data Scientist, you will leverage your skills and expertise in data science, machine learning, and artificial intelligence to extract valuable insights from large and complex data sets.. Collect, clean, and preprocess data from various sources, such as databases, APIs, web scraping, or surveys. Deploy and integrate the models and algorithms into production systems and applications, using tools such as Flask, Docker, or Kubernetes. Expertise in data science, machine learning, and artificial intelligence concepts, methods, and techniques, such as regression, classification, clustering, natural language processing, computer vision, or deep learning. Proficient in machine learning and deep learning tools and libraries, such as TensorFlow, PyTorch, Scikit-learn, or Keras

We are seeking a highly skilled and experienced Sr. Machine Learning Engineer / Data Scientist to join our dynamic Data Science and AI team. Utilize advanced machine learning techniques (e.g., deep learning, NLP, computer vision, reinforcement learning) to create innovative solutions. Expertise in Python and proficiency in ML frameworks (TensorFlow, PyTorch, scikit-learn). Technical Proficiency: Proficiency in cloud platforms such as Azure Synapse Analytics, Azure Machine Learning, AWS, and Google Cloud Platform for deploying big data and ML solutions. We do not discriminate or allow discrimination on the basis of race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), age, sexual orientation, gender identity, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, disability, status as a crime victim, protected veteran status, political affiliation, union membership, or any other characteristic protected by law.

We provide extensive expertise in Synthetic Aperture Radar (SAR) image processing algorithm development, computer vision, modeling and analysis of radar systems & pattern recognition technologies.. We are looking to add an experienced Machine Learning Engineer to our esteemed team who can develop cutting edge Deep Learning technologies in the domains of Computer Vision, Synthetic Aperture Radar (SAR), and Geospatial Exploitation.. Position Overview : The Machine Learning Engineer - Deep Neural Networks will develop, train, and deploy machine learning algorithms and neural networks to solve challenging real-world problems.. 1-5+ years of experience in Machine Learning (ML), Data Science, and Artificial Intelligence (AI), ideally with deep learning experience. Ideally you've worked with most or some of the following: Computer Vision, Radar, SAR, Lidar, Matlab, Deep Neural Networks, pandas, NumPy, Keras, PyTorch, scikit-learn, and open source frameworks

The ideal candidate has a robust understanding of machine learning, data science, and algorithm development.. Skills Required: Experience with Python, R, or Java, and ML libraries such as TensorFlow, PyTorch, and scikit-learn.. Proficiency in handling large datasets, and cloud services like AWS, GCP, or Azure.. Strong understanding of deep learning, NLP, or computer vision (as applicable).. Knowledge of big data tools (e.g., Apache Spark, Hadoop).

As a Data Scientist in our team, you will work on data science projects across the company with the purpose of solving complex business problems by applying advanced methods including artificial intelligence, machine learning, causal inference, advanced statistics, computer vision, natural language processing and other related techniques.. You will also design and build computational models, discovering insights and identifying opportunities using statistical and algorithmic methods as well as data visualization techniques.. Experience with big data tools (Hadoop, Spark) and scripting languages (PHP, Perl, Bash).. Expertise in relevant methods and skills such as data wrangling, EDA, data visualization, prototyping, feature engineering, dimensionality reduction, classification methods, regression methods, clustering methods, computer vision methods, time-series analysis, causal inference, NLP.. Knowledge for API usage, web scraping and text processing

Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence, and apply new techniques to improve existing processes and models. 5+ years of experience in data science, with a focus on machine learning, predictive modeling, and advanced analytics. Proficiency in programming languages such as Python, R, and SQL, with experience in libraries and frameworks like TensorFlow, PyTorch, Scikit-learn, and Pandas. Strong understanding of statistical methods, data mining, and machine learning algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning. Experience working with large datasets, cloud computing platforms (e.g., AWS, GCP), and big data technologies (e.g., Spark, Hadoop).

We are seeking a machine learning engineer who will strive to turn huge amounts of data into actionable insights that improve safe customer experience.. This role requires exceptional collaboration across Data Science, Software Engineering, and Machine Learning Research.. You'll work with partner teams to develop strategic, long-term fraud prevention solutions while continuously enhancing your software engineering and machine learning expertise.. 3+ years of experience with big data tools (SQL, Spark, Splunk, Python, Jupyter Notebook).. Experience with Python, Scala, Java, or similar, including relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Spark MLlib).

Domain Exposure: Healthcare, Pharmaceuticals, Manufacturing, Banking & Finance, Utilities/ Energy, Insurance, Retail, Government, Telecom, Aerospace/ Airlines, Education, Real Estate, Oil & Gas, IT/Software, Media/ Entertainment. Ph. D. degree in Artificial Intelligence, Machine Learning, Robotics, Computational Neuroscience or related technical field with a strong publication/practical implementation or any field. Strong deep learning, particularly in applications of Neural Network architectures to Computer Vision, Natural Language Processing, Machine Intelligence and/or Reinforcement Learning. One or more deep learning frameworks such as Pytorch, Torch, Caffe, or Tensorflow. Research focus on one of the following: Computer Vision, Deep Reinforcement Learning, NLP, ASR, Audio Processing