Data Science & Machine Learning Jobs

NLP/DL Quantitative Research - Chicago, New York. A leading multi-strategy hedge fund is expanding its systematic equities team and is seeking a Quantitative Researcher with deep expertise in Natural Language Processing (NLP) and Machine Learning (ML).. This is a rare opportunity to work in a newly formed Senior PM pod, leveraging alternative data, tick-by-tick market data, and deep learning models to drive innovative trading strategies.. Proven track record in machine learning, deep learning, and NLP applications. Strong programming skills in Python, TensorFlow, PyTorch, or similar frameworks

We are seeking a Machine Learning Engineer with approximately 5 years of experience in the field.. Toolchain Expertise: Utilize and integrate modern toolchains and frameworks (e.g., TensorFlow, PyTorch, Hugging Face) to build and deploy machine learning models.. Cloud Operations: Manage and optimize machine learning workflows in cloud environments (e.g., AWS, Google Cloud, Azure), ensuring scalability and efficiency.. Cloud Operations: Experience with cloud platforms (AWS, Google Cloud, Azure) and knowledge of cloud-based machine learning services and deployment strategies.. Toolchain Knowledge: Familiarity with machine learning frameworks and tools (e.g., TensorFlow, PyTorch, Hugging Face Transformers) and version control systems (e.g., Git).

Role: Data ScientistPlano, TX (Hybrid)Duration: 12+ Months Contract What you bring: Strong experience manipulating data set and building statistical models, has master's or Ph. D. in statistics, mathematics with focus on ML, NLP, machine learning or another quantitative field.. Strong Knowledge and experience in statistical and data mining techniques - GLM/regression, Random Forest, Boosting, text and data mining.. Experience querying database and using statistical computer languages : R , Python, SQL etc.. Exp leveraging big data and search technologies (e.g., Spark, Elastic Search, Natural Language Processing, Web Crawling).. Knowledge of machine learning techniques and algorithms and be able to apply them in data driven natural language processing techniques.

As a staff engineer, you will partner closely with our data science, product partners, and other ML + data engineers on the team to execute on these opportunities in order to improve the Host and Guest product experience on Airbnb.. Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases.. gradient boosted trees, neural networks/deep learning, optimization, state-of-art NLP and CV algorithms) and domains (eg.. Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg.. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity.

The Ad Platforms Data Insights team is seeking a machine learning engineer to join in developing the next generation of analytical solutions working with Engineering, Sales, Product, Marketing, and Finance!. Do you have experience in applied research with expertise in pattern mining, anomaly detection, text analytics, predictive modeling, classification, and optimization?. Comfortable with cloud technologies such as AWS, Snowflake.. Familiarity with job orchestration frameworks like Airflow, CICD, model serving, scalability, Kubernetes, Docker, Jenkins.. Experience in deep learning, LLM fine-tuning, and/or natural language processing.

Lead Python Application Developer needs 7+ years overall experience with 1-3 years in an ESG technology focused role within asset management or financial services industry.. Experience with machine learning tools such as scikit-learn, R, Theano, TensorFlow, SparkML, or Foundry. Demonstrates functional knowledge of data visualization libraries such as matplotlib or ggplot2; knowledge of other visualization tools such as Microsoft Power BI , Quick Sight or Tableau.. Knowledge of cloud & computing technologies such as: Hadoop, Apache Spark, AWS, Microsoft Azure or Google cloud.. Leverage a broad set of modern technologies including Python, R, Scala, and Spark to analyze and gain insights within large data sets and implement systems for automatic data collection, curation and model training

2024 Fall Co-Op - Machine Learning Engineer (NLP & Vision) Walmart Advanced Systems & Robotics, formerly known as Alert Innovation, is now an integral part of the global Walmart organization.. Knowledge in machine learning, deep learning, NLP, and Computer Vision.. Proficiency in Python and familiarity with machine learning frameworks such as TensorFlow, PyTorch, or Keras.. Responsibilities: Assist in the development, implementation, and optimization of machine learning models and algorithms for NLP and Computer Vision applications.. Conduct research on cutting-edge techniques and tools in machine learning, NLP, and Computer Vision.

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”.

Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).. Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems. Python, PHP, or Haskell. Linux, UNIX, or other *nix-like OS as evidenced by file manipulation, advanced commands, and shell scripting. Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction

You speak math and enjoy dissecting the intricacies of machine learning, deep learning, and algorithms at the most fundamental level.. You are required to be in the office 3 days a week in Round Rock, TX, just outside of Austin.. Deep learning frameworks such as PyTorch, TensorFlow, or Keras. Modern deep-learning techniques for NLP. Machine learning techniques and predictive analytics (e.g., deep learning, regression, classification, clustering, unsupervised learning)

Learn and apply state-of-the-art data science practices as a member of an interdisciplinary team. Apply techniques from natural processing (NLP) to understand textual data, including named entity recognition, topic modeling, and sentiment analysis. Proficient in one or more programming for data manipulation and analysis, such as Python, R, SQL, C, C#, C. Experience with various data visualization tools such as Tableau, Qlik Analytics, MS Power BI, Plotly, or Matplotlib. Experience with “big data” tools such as Hadoop, Spark, Kafka, Databricks, or Palantir Foundry is

CAIS is the pioneer in democratizing access to and education about alternative investments for independent financial advisors, empowering them to engage and transact with leading asset managers on a massive scale through a wide variety of alternative investment products and technology solutions.. CAIS provides financial advisors with a broad selection of alternative investment strategies, including hedge funds, private equity, private credit, real estate, digital assets, and structured notes.. As a Machine Learning Specialist / Data Scientist, you will play a pivotal role in shaping the future of predictive modeling within the alternative asset management and wealth management space.. Design and develop models for portfolio optimization, recommendation systems, propensity models, lead scoring, time series forecasting, and risk analysis using a combination of classical statistical methods, machine learning algorithms and novel deep learning algorithms.. Cloud deployment expertise, including Kubernetes, Docker and/or cloud ML platforms such as Amazon SageMaker.

The candidate will be working with other data engineers, data analysts and data scientists to focus on applying data engineering, data science and machine learning approaches to solve business problems.. As a senior member of the Data Engineering & Analytics team, you will be building machine learning and artificial intelligence products to uncover customer, product and operational insights.. Effective advanced analytics and AI skills with a foundation in programming (e.g. R, python), database environment (e.g. big-data platforms and SQL skills), and dashboard development. Strong programming (e.g. Python / Java / Kotlin) and data engineering skills.. Machine learning frameworks such as Keras, PyTorch, or Tensorflow

Stay updated on advancements in data science, machine learning, and analytics.. Hands on experience working on analytical platforms like Ruby, R, Python, Azure MLExperience in Data science model review, code refactoring optimization, containerization, deployment and monitoring ML modelsExperience in Data science Model testing, validation and Test Automation.. Expertise in Data visualization tools such as Power BI, Tableau and LookerAbility to understand API Specs, identify relevant API calls, extract data and implement data pipelines & SQL friendly data structures.. Strong knowledge of statistical techniques, machine learning algorithms, and data mining techniques.. Proficient in any of the following applied analytical techniques - clustering, regression analysis, time series analysis, NLP, neural networks, KNN, association rules, decision trees, logistic regression or similar.

Job Description :We are looking for a seasoned Machine Learning Engineer specialized in Large Language Models (LLMs) to drive the development and deployment of cutting-edge AI solutions.. The ideal candidate will have extensive experience in deep learning and NLP, specifically with advanced models such as GPT-3, BERT, Transformer architectures, and Retrieval-Augmented Generation (RAG) models.. Ensure the stability and efficiency of machine learning models by leveraging Bedrock for hosting and managing deployed models.. Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.. Experience with cloud computing platforms (, AWS, Azure, GCP) and cloud native computingProficiency in programming languages like Python, Java, Scala, C#, SQLExpertise in big data technologies such as Hadoop, Spark, Kafka, and NoSQL databasesKnowledge of data modeling, ETL processes, and data warehousing conceptsExceptional problem-solving abilities and teamwork skills.

We are seeking a talented and experienced Data Scientist to join our team onsite at Warner Robins Air Force Base (AFB), GA. This role is integral to harnessing data to support mission-critical decisions in a secure defense environment.. Perform data mining, statistical analysis, and predictive modeling.. Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI).. Experience with big data technologies Hadoop, Spark) and cloud platforms AWS, Azure).. Experience with natural language processing (NLP) and deep learning frameworks TensorFlow, PyTorch).

The systems run in the Cloud so we always think cloud first!. We are removing barriers that keep the product team from executing faster than our competitors and releasing a clean, quality product.. This means supporting & testing our stack in a public cloud as well as with distributed schedulers, logging solutions, metrics, storage archiving, and optimization of HPC application cost & performance.. About the Job The candidate will work closely with HPC engineers to build reusable components for generating real-time insights and analytics for HPC simulationsThe candidate will also assist in Research & Development for our next generation machine learning products in Network SimulationsThe candidate is expected to have experience working with data pipelines and ML frameworks.. Minimal requirements Experience using statistical computer languages (Python, Golang, SQL, etc.)

· Expert level in Designing and Architect solutions in Azure Data factory, Azure Databricks, Azure Datalake, Delta Lake and Azure synapse analytics implementation.. · Experience in Azure cloud technologies like PySpark, Synapse, ADF, Databricks, Python, Scala and SQL. · Have good experience configuring Microservices using Docker, Kubernetes on Azure Data Bricks Extensive Experience on working on Azure AI services including Data Bricks and Azure cognitive services.. Hands-on experience on design, and optimizing LLM, natural language processing (NLP) systems, frameworks, and tools.. · Prototypes and do proof of concepts (PoC) in one or all the following areas: · LLM, NLP, DL (Deep Learning), Client (Machine Learning), object detection/classification, tracking, etc.. · Stay up to date with the latest advancements in LLM, NLP, deep learning, machine learning, and object detection algorithms, and proactively identify opportunities to leverage new technologies for improved solutions.

Python, R, PySpark, Juoyter Lab, Pycharm − Exploratory Data Analysis, Visual Analytics − Oracle, MySQL − Windows, Linux − A/B Testing − Hadoop, Spark, MLlib, Git − Design of Experiments (DoE) − Natural Language Processing (NLP) models − Pandas, Numpy, Matplotlib, Scikit Learn, Scipy and NltkTK in Python for developing various machine learning algorithms.. − Leadership and Communication Skills − ML Algorithms: LR, SVM, Ensemble Trees, Matrix Factorization, Neural Networks, Clustering Analysis, Dimensionality Reduction Algorithms, Optimization problems a plus Experiences. Experience in linear algebra, especially sparse systems. Developed forecasting model to predict revenue using Python libraries.. Candidate should be very client oriented, proactive, innovative, problem solver

Design, develop, train, evaluate and deploy systems using various Deep Learning and Machine Learning Algorithms. 0-2 years of work or educational experience in Computer Vision / Deep Learning or Machine Learning. Experience with OpenCV or other computer vision libraries. Experience in using a machine learning framework such as TensorFlow, Scikit-learn, OpenCV, Keras, Torch and Caffe. Experience with Natural Language Processing (NLP) is a plus