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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.
We at Innovaccer are looking for a Staff Engineer specializing in Artificial Intelligence (AI) who leads the design, development, and deployment of advanced AI systems.. Design, build, and optimize machine learning (ML) and deep learning (DL) models, including generative AI frameworks like transformers and GANs. Experience with natural language processing (NLP), computer vision (CV), or other specialized AI domains.. Experience with big data tools (Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud).. Leading healthcare organizations like CommonSpirit Health, Atlantic Health, and Banner Health trust Innovaccer to integrate a system of intelligence into their existing infrastructure— extending the human touch in healthcare.
Strong knowledge of machine learning algorithms, deep learning frameworks (TensorFlow, PyTorch), and statistical modeling. Hands-on experience with MLOps, CI/CD for machine learning, and containerization tools (Docker, Kubernetes). Familiarity with natural language processing (NLP), computer vision, or reinforcement learning is a plus. Experience with large-scale data processing frameworks such as Apache Spark. LaSalle Network is the premier staffing and recruiting firm, earning over 100 culture, revenue and industry-based awards from major publications and having its company experts regularly contribute insights on retention strategies, hiring trends and hiring challenges, and more to national news outlets.
As a dedicated Director, Data Scientist, you will lead a team of Data Scientists responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions to inform actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations. 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master’s, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis. Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc. Experience in developing and reviewing modeling solutions based on broad range of techniques – e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques.
Strong background in ML frameworks (TensorFlow, PyTorch, Scikit-learn) and distributed computing.. Expertise in cloud platforms (Azure, GCP or AWS) and containerization (Docker, Kubernetes).. Experience with database systems (SQL, NoSQL) and big data frameworks (Spark, Hadoop) is a plus.. Experience with model optimization techniques such as distillation, quantization, and hardware acceleration.. Advanced certifications in cloud computing, machine learning, or DevOps is a big plus.
This is a 12+ Months Contract opportunity with long-term potential and is located in Richmond VA (Hybrid).. Skills- Hadoop, Python, Machine Learning. Deep knowledge of machine learning, data mining, statistical predictive modeling, and extensive experience applying these methods to real world problems.. Extensive experience in Predictive Modeling and Machine Learning: Classification, Regression & Clustering.. Understanding and experience working on Big Data Ecosystems is preferred : Hadoop, HDFS, Hive, Sqoop, Spark: pySpark, SparkR, SparkSQL, Jupyter & Zeppelin notebooks.
We are looking for a Machine Learning Scientist / Engineer who will be converting abstract, high-level goals into concrete, measurable requirements.. Deep learning, computer vision, topic modeling, graph algorithms are pluses. Strong programming skills and hands-on experience with machine learning tools and libraries such as PyTorch, TensorFlow, Scikit-learn; programming skills in Scala, Python, Java, or C. Knowledge of Spark, Apache Hadoop, Solr/Lucene, Cassandra, and related big data technologies. Masters or PhD degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields.
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
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”.
State of the art prediction models for estimating food preparation times, batching quality as well as time spent by couriers at restaurants picking up items. You will be in-charge of solving Uber scale problems with the right techniques like reinforcement learning/deep learning/optimization methods. Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib.. Experience with SQL and database systems such as Hive, Kafka, Cassandra, etc.. Experience in modern deep learning architectures and probabilistic models.
As a dedicated Director, Data Scientist, you will lead a team of Data Scientists responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions to inform actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations. 8 years in predictive modeling, model governance, machine learning and large data analysis., OR Advanced Degree (e.g., Master’s, PhD) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative STEM field (Science, Technology, Engineering and Math) field and 6 years in predictive modeling, model governance, machine learning and large data analysis. Experience with various languages, applications, and technologies (such as SQL, Python, R, Spark, Hadoop etc. Experience in developing and reviewing modeling solutions based on broad range of techniques – e.g., linear and logistic regressions, time series methods, survival analysis, support vector machines, neural networks, decision trees, random forests, gradient-boosting methods, deep learning, k-means and other clustering methods, simulation methods, or other advanced techniques.
Leverage Microsoft Azure cloud tools for model training, deployment, and monitoring.. Develop and integrate LLM-based solutions into real-world business applications.. Proficiency in Python or R, with hands-on experience using ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.. Deep understanding of Azure services including Azure Machine Learning, Cognitive Services, and Data Factory.. Knowledge of NLP, computer vision, or predictive modeling.
Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms.. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more.. Experience with machine learning libraries like TensorFlow, Pytorch, Scikit-learn, etc.. Familiarity with big data technologies (e.g., Spark, Hadoop) and data visualization tools.. A multinational organization with 58 offices in 21 countries and the possibility to work abroad
Our client, an early-stage startup that is innovating how individuals and financial institutions navigate government policy changes, is seeking a Data Scientist for a direct hire position.. You will be integral to the research, development, and productionalization of advanced analytical methods, including Artificial Intelligence, Machine Learning, and Predictive Analytics.. 5+ years of experience in data science, with a focus on machine learning, predictive modeling, and data analytics.. Proficiency in Python (pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) and SQL.. Experience with NLP, deep learning frameworks, and large language models (LLMs), including prompt engineering, retrieval-augmented generation, and fine-tuning.
Implement best practices for data management, including data governance and documentation.. Strong proficiency in SQL and experience with relational databases (e.g., SQL Server, MySQL, PostgreSQL).. Experience with machine learning frameworks and libraries like scikit-learn, TensorFlow, PyTorch.. Proficiency in data visualization tools using Power BI. Familiarity with cloud platforms specifically Azure.. Understanding of data governance and data security best practices.
Utilize frameworks such as Scikit Learn, TensorFlow, PyTorch, Vertex AI, and Azure AI Studio. Experience implementing multiple machine learning techniques such as supervised, unsupervised, reinforcement learning, Deep learning, NLP. Solid technical writing skills and must have published research papers in leading academic journals on topics related to Artificial Intelligence & Machine Learning. Proven sound understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life.
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).
At Zoom, we help people stay connected and enhance collaboration through products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinar.. Have hands-on experience developing AI/ML solutions, including LLMs, deep learning, NLP, and reinforcement learning, using frameworks like TensorFlow, PyTorch, Keras, and Scikit-learn.. Be proficient in designing ETL pipelines for large datasets; familiar with Airflow, Hadoop, Spark; experienced with RDBMS (Oracle, MySQL, MS SQL) and NoSQL (MongoDB, MariaDB).. Have knowledge of Kubernetes, containers, and CI/CD for AI/ML; experience with AWS, GCP, or Azure AI/ML services; skilled in debugging and optimizing large-scale data performance.. Our structured hybrid approach is centered around our offices and remote work environments.
In HADOOP , you'll be given an introduction to BIG DATA, APACHE HADOOP, HADOOP ECOSYSTEM, CLOUDERA QUICKSTART VM along with core concepts of the Hadoop framework including MapReduce, HIVE, PIG, SQOOP, FLUME, HBASE, OOZIE.. Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science.. In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.. Web scraping using Python Beautiful soup.. What is web scraping (Difference between web scraping software vs a web browser) , what is parser?
On Site Hybrid if you reside in Tampa, FL area Remote- available Work Authorization: (No future sponsorship) US Citizens or Green Card Only No relocation Data Scientist/Analyst – AI Job Summary We are looking for a seasoned Data Scientist with a minimum of 7 years of experience in data science with a focus on Generative AI to collaborate closely with our AI Product Director in the rapid development and delivery of AI solutions for the ACA healthcare industry.. The ideal candidate will have a wide breadth of expertise in data science with special emphasis on predictive modeling and forecasting as well as proficiency in Python, SQL, TensorFlow, and experience using platforms such as Google Vertex AI and NVIDIA NeMo. Experience in data preprocessing using tools like Alteryx and Google Dataflow is also essential.. Proficient in Python and SQL, TensorFlow, and experience using platforms such as Google Vertex AI and NVIDIA NeMo Machine Learning Algorithms: Classical Models: Experience in developing models like Linear Regression, Logistic Regression, and Random Forest.. Natural Language Processing (NLP): Experience in text analytics using models like BERT, GPT, or LSTM. Computer Vision: Familiarity with image recognition models like YOLO, Faster R-CNN, or Mask R-CNN. Experience with Machine Learning Frameworks: TensorFlow: Proficiency in developing and deploying machine learning models.. Familiarity with Google Vertex AI and NVIDIA NeMo: For model development, deployment, and scaling.