Data Science & Machine Learning Jobs

Strong proficiency in Python, R (must-have) with experience in libraries such as Scikit-learn, and TensorFlow/PyTorch. Expertise in supervised and unsupervised machine learning techniques, including regression, classification, clustering, anomaly detection, and deep learning. Hands-on experience with Dataiku for end-to-end data science and data visualization tools (e.g., Looker, Power BI). Experience within Hi-Tech / Telecommunication specific industry/domain such as Supply Chain, Accounting, Sales etc. Non-Sales employees may be eligible for a discretionary incentive bonus, while Sales employees may be eligible for a sales commission.

The goal of a Machine Learning Engineer at Scale is to bring techniques in the fields of computer vision, deep learning and deep reinforcement learning, or natural language processing into a production environment to improve Scale's products and customer experience.. Extensive experience using computer vision, deep learning and deep reinforcement Learning, or natural language processing in a production environment. Strong programing skills in Python or Javascript, experience in Tensorflow or PyTorch. Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization. AWS or GCP) and developing machine learning models in a cloud environment

He will independently and in collaboration with others, research, design, develop, and implement innovative Machine Learning, AI, deep learning, NLP, Cloud, Data Science solutions that will advance NYSE's analytics capabilities across multiple business lines.. 2 or more years of experience in applying AI/ML/ NLP / deep learning / data-driven statistical analysis & modelling solutions to quantitative analysis to financial market data.. Strong Knowledge of the theory and applications of machine learning, AI, deep learning, data science, NLP, text analytics, unstructured data analytics, supervised/unsupervised learning.. Java, R , MATLAB, Scala, and with machine learning and deep learning and Big data frameworks including TensorFlow, Caffe, Spark, Hadoop.. Proven capability in demonstrating successful advanced technology solutions (either prototypes , POCs, well-cited research publications, and/or products) using ML/AI/NLP/data science in one or more domains,

Senior Machine Learning Engineer. New opening for a Machine Learning Engineer to lead a growing team within digital, gaming and streaming media.. The team is creative with machine learning, predictive modeling, and deep learning.. Develop advanced AI/LLM data driven pipelines to fuel our analytics platform.. Create and apply advanced machine learning and deep learning solutions to extract insights from diverse structured and unstructured data sources.

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.

We are seeking a Principal Applied Machine Learning Engineer to be the foundational hire responsible for establishing the company's machine learning capabilities.. Develop models for classification, regression, NLP, and LLM-based use cases, aligned to critical business needs in operations, payments, and product workflows.. Deep hands-on experience with AWS ML services, especially SageMaker and Bedrock.. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.. Familiarity with big data tools like Spark, Kafka, or Hadoop.

AI: Machine Learning, Deep Learning, Scikit, Spark ML, TensorFlow, Keras, NLP (spacy, nltk). AWS SageMaker, Ray Distributed systems / Big Data: Spark, Kafka, Hadoop, HBase, Cassandra. Data Science: Python data analytics ecosystem (Pandas, Scikit, etc). Datastores: Vector stores (MongoDB Atlas, Milvus), NoSQL’s (HBase, Cassandra, MongoDB, Redis), and SQLs (Postgres, MySQL). DevOps / Tools: Docker, Kubernetes, Ansible, Terraform, Linux, git

COMPANY The Company specializes in digital enablement and transformation using industry-leading process mining, data management and automation platforms.. They help Fortune 500 companies become more process-efficient and improve their end-customer experience through the use of RPA, AI & ML powered solutions.. POSITION SUMMARY we are looking for a Senior Data Scientist to help drive actionable insights using artificial intelligence and machine learning algorithms.. The candidate should conduct and manage analysis and modelling in the areas of machine learning, neural networks, robotics etc.. KEY RESPONSIBILITIES Work with business partners within one business process to align technology solutions with business strategies.

Has obtained a Ph. D. degree in Machine Learning, Artificial Intelligence, Computer Science, Information or Multimedia Retrieval, Reinforcement Learning, Mathematics, or relevant technical field.. Experience with deep learning frameworks such as Pytorch or Tensorflow.. Experience building systems based on machine learning, reinforcement learning and/or deep learning methods.. Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICLR, AAAI, RecSys, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, EACL, ICASSP, or similar.. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

We are seeking a high energy, driven, and innovative Director of Data Science & Machine Learning Engineering to join our Data Science CoE in Berkeley Heights, NJ. The Data Science CoE aims to provide solutions but also grow Axtria’s footprint and business in the AI/GenAI & ML Ops Engineering space. Expertise in advanced AI/ML algorithms & their applications, NLP, deep learning frameworks, computer vision. Ability to build scalable models using Python, R-Studio, R Shiny, PySpark, Keras, Tensorflow.. Relevant mastery in Feature Engineering, Feature Selection and Model Validation on Big Data. Familiarity with cloud technology such as AWS / Azure and knowledge of AWS tools such as S3, EMR, EC2, Redshift, Glue; viz tools like Tableau and Power BI.

Designs and implements Machine Learning (ML) and Deep Learning (DL) algorithms across multiple projects. Programs ML frameworks using Python and R. Develops and models software solutions utilizing Natural Language Processing (NLP), Information Retrieval, Machine Comprehension, Question Answering/Conversational AI, Reinforcement Learning, Knowledge Graphs, Causal Inference, and Experimental Design. Conducts exploratory data analysis, predictive analytics, and prescriptive analytics leveraging Big Data, NLP, and chatbot technologies such as Elasticsearch and Solr. Promotes the use of ML and DL frameworks like TensorFlow, Keras, MXNET, and H2O. Expertise in predictive modeling, training, and evaluating ML algorithms using Python and frameworks like scikit-learn, TensorFlow, PyTorch, Keras, especially in Conversational AI and Search applications. Experience designing NLP and NLU solutions such as Chatbots, Information Retrieval, NER, Summarization, and Text classification using NLP, ML, DL, and embedding techniques like LSTM and BERT.

Director, Artificial Intelligence and Machine Learning (AI/ML) Quality Oversight Director, Artificial Intelligence and Machine Learning (AI/ML) Quality Oversight United States - Maryland - Frederick, United States - California - Santa Monica, United States - California - Oceanside Quality Regular. Job Description We are seeking a highly experienced Director of Artificial Intelligence and Machine Learning (AI/ML) Quality Oversight to establish and lead the quality assurance strategy for our AI/ML initiatives, specifically within a Good Manufacturing Practice (GMP) environment.. Ensure the quality and reliability of Natural Language Processing (NLP) solutions developed for tasks including sentiment analysis and automation.. PhD in degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field with 8+ years of progressive experience in developing and deploying machine learning models and AI solutions, with a strong emphasis on quality assurance and oversight OR. Hands-on experience with NLP, deep learning frameworks (e.g., TensorFlow, PyTorch), and deploying models in production environments, with a quality-centric approach.

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.

Its patent-pending approach uniquely combines advances in data science and technology (AI, machine learning, cloud computing) to transform risk management.. Deep understanding of machine learning/statistical algorithms such as time series analysis and outlier detection, neural networks/deep learning, boosting and reinforcement learning.. Expertise in an analytical language (Python, R, or the equivalent), and experience with databases (GCP, SQL, or the equivalent). Experience in building NLP solutions and/or GEN AI are strongly preferred. 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy

Profound experience and theoretical understanding of advanced quantitative methods in statistical, machine learning and deep learning. Extensive experience with SQL, Python, and machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).. Significant experience with cloud platforms (e.g., AWS, Microsoft Azure, Databricks, Kubernetes).. Experience in advanced modeling techniques, including numerical optimization algorithms, natural language processing (NLP), large language models (LLM) and reinforcement learning.. Access to additional benefits like mental healthcare as well as fertility and adoption assistance.

About the job Data Science Analyst r. Create and use advanced machine learning algorithms and statistics: regression, distributions, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.. Work to analyze data from a wide variety of 3rd party data providers: Google Analytics, Adwords, Adobe, etc.. Use distributed data/computing tools to achieve business results: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.. g S3, Spark, DigitalOcean, Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL

The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.. As an Executive Director on the Machine Learning Center of Excellence (MLCOE) team, you will be responsible for applying advanced machine learning techniques to a variety of complex tasks.. These tasks include natural language processing, speech analytics, time series, reinforcement learning, and 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 (.. : TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.

Job Title: Big Data Machine Learning Engineer. Hadoop, Machine Learning, Java/Scala/Python, Apache Spark, Predictive Modeling, Industrial IoT Analytics, Data Visualization, Natural Language Processing (NLP). Bachelors in Computer Science or Equivalent- Preferred Masters or PhD in Machine Learning, Data Analytics, Big Data or similar. Machine Learning- production implementation not just building the prototypes. Well versed in the Big Data world; candidate should know at least what each of the followings are and should have extensive experience with some: Hadoop, Pig, Hive, Spark, Lambda Architecture, Apache Storm/Samza, Kafka, MR, Oozie/Airflow/

From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Successful candidates will be an expert in using state-of the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications in healthcare, diagnostics, hospital operations, and more. Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc. 6+ years of experience working in data science, data engineering, software engineering, or MLOps.. 6+ years of experience in core programming languages and data science packages (Python, Keras, Tensorflow, PyTorch, Pandas, Scikit-learn, Jupyter, etc.)

Role: Data Scientist - AI Strategy & Implementation(This role is open to US Citizens, Green Card holders, GC-EAD only.. As a Data Scientist / Data Analyst / Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.. Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation-systems, environmental systems and/or agronomic problems.. Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes. Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines constructionMust have