Senior Manager Data Science

Senior Data Scientist II

Senior Data Scientist

Corporate Risk Analyst

Data Engineer / Senior / Supervisor

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions</li><li>Lead the development of AI and machine learning models to solve business problems</li><li>Research, build, and deploy models based on shallow and deep machine learning</li><li>Train robust NLP-based models on large datasets</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs</li><li>Design APIs for disseminating data science outputs</li><li>Oversee the scaling of production systems to meet growing demands</li></ul> Requirements: <ul><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

About the Role : <ul><li>As a data scientist on our team, you will work on new product development in a small team environment writing production code in both run-time and build-time environments.&nbsp;</li><li>You will help propose and build data-driven solutions for high-value customer problems by discovering, extracting, and modeling knowledge from large-scale natural language datasets including matter and contract repository, invoice/legal spend data and work management.&nbsp;</li><li>You will prototype new ideas, collaborating with other data scientists as well as product designers, data engineers, front-end developers, and a team of expert legal data annotators.</li><li>You will get the experience of working in a start-up culture with the large datasets and many other resources of an established company.</li><li>We are committed to advancing gender diversity within the technology sector and supporting greater representation of women in tech. To further this commitment,</li></ul> Responsibilities: <ul><li>Develop and implement LLM-based applications tailored for legal use-cases&nbsp;</li><li>Evaluate and help maintain our data assets and training/evaluation data sets&nbsp;</li><li>Design and build pipelines for preprocessing, annotating, and managing legal document datasets&nbsp;</li><li>Collaborate with legal experts to understand requirements and ensure ML-applications meet domain-specific needs&nbsp;</li><li>Conduct experiments and evaluate model performance to drive continuous improvements&nbsp;</li><li>Fine-tune and deploy large language models to enhance their performance on legal text processing tasks&nbsp;</li><li>Interface with other technical personnel or team members to finalize requirements.&nbsp;</li><li>Work closely with other development team members to understand complex product requirements and translate them into software designs.&nbsp;</li><li>Successfully implement development processes, coding best practices, and code reviews for production environments.</li></ul> Requirements:&nbsp; <ul><li>Able to work in person 2 days per week&nbsp;</li><li>Bilingual English and Spanish&nbsp;</li><li>Practical experience with large language models, prompt engineering, fine-tuning RAG-based applications and benchmarking, using frameworks such as LangChain&nbsp;</li><li>MS in Data Science, Computer Science, Statistics, Machine Learning, or relevant work experience&nbsp;</li><li>Practical experience in Natural Language Processing methods and libraries such as spaCy, word2vec, Flair, BERT (ways to vectorize text data)&nbsp;</li><li>Formal training in machine learning: dimensionality reduction, clustering, embeddings, and sequence classification algorithms&nbsp;</li><li>Strong Python background&nbsp;</li><li>Knowledge of AWS, GCP, Azure, or other cloud platform&nbsp;</li><li>Understanding of data modeling principles and complex data models.&nbsp;</li><li>Proficiency with relational and NoSQL databases as well as vector stores (e.g., MySQL, Postgres, Solr, Elasticsearch/OpenSearch)</li><li>Knowledge of Spark-Scala, Ray or other distributed computing systems highly preferred&nbsp;</li><li>Knowledge of API development, containerization, and machine learning deployment highly preferred&nbsp;</li><li>Experience with ML Ops/AI Ops including experiment tracking tools like LangFuse and DVC&nbsp;</li><li>Experience with deep learning frameworks such as PyTorch, Tensorflow and Hugging Face Transformers Work in a way that works for you We promote a healthy work/life balance across the organization. </li><li>We offer an appealing working prospect for our people.&nbsp;</li><li>With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate. </li><li>Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.</li></ul>

Responsibilities: <ul><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems. Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units. Overseeing the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Leading the development of advanced AI and machine learning models to solve complex business problems Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Leading the automation and lifecycle management of sophisticated data systems.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Designing APIs for disseminating data science outputs to various business units.</li><li>Overseeing the scaling of production systems to meet growing demands.</li></ul> Requirements: <ul><li>Possess an advanced or Masters education in Computer Science, Mathematics, Statistics, or a related field. Have experience working directly with large language models and transformer-based architectures including BERT, RoBERTa, T5 etc.</li><li>Be proficient in working with big data technologies and tools like Hadoop, Spark, or AWS.</li><li>Have experience and knowledge of applying LLMs including ChatGPT, GPT 3.5, Claude, Mistral, etc.</li><li>Be a natural problem solver, able to lead and mentor junior data scientists, and collaborate with cross-functional teams.</li><li>Demonstrate proficient experience with machine learning algorithms, including deep learning, gradient boosting, and random forests Possess advanced programming skills in Python, R, or other relevant languages for data analysis.</li></ul>

Responsibilities: <ul><li>Apply open- and closed-source collection and analysis skills to author threat and risk intelligence reports and briefings. Identify and assess all-risk events and/or changes in the operating environment that have the potential to impact company people or operations.</li><li>Serve as generalist with broad knowledge of information collection protocols and company global risk priorities while maintaining subject matter expertise within their region.</li><li>Stay up to date on global developments, including but not limited to geopolitics, relevant regulation, natural hazards, physical and cybersecurity, industry trends, and organizational changes that might influence company people, operations, or shareholders.&nbsp;</li><li>Ensure the timely and accurate communication of risk information to ERSM and cross-functional leaders to support business decision makers and crisis management efforts.&nbsp;</li><li>Support the regional ERSM leader in the execution of security and resilience programs administration, travel safety, data integrity, compliance tracking, and reporting.</li><li>Support the development of key strategic deliverables, such as risk modeling, recurring emerging risk reports, and bespoke customer-driven requests.</li><li>Develop and maintain technical knowledge of systems and data. Develop and maintain datasets from various internal and external sources to identify trends, extract insights, and measure performance.</li><li>Engage with relevant risk information and industry networks to develop and maintain appropriate skillsets and cultivate a professional network.</li><li>Work collaboratively as well as independently to advance the security and resilience of company people and operations around the world.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s degree, local educational equivalent, or commensurate experience in relevant fields.</li><li>Advanced / native fluency in English and Chinese languages (speaking and writing).</li><li>Additional language proficiencies are a plus.&nbsp;</li><li>Strong organizational, written, and verbal communications skills, including exceptional time management.</li><li>Skilled using Microsoft Office 365 (Word, PowerPoint, Excel, Teams, etc.).</li><li>Familiarity with data management tools (e.g., MS Excel, SharePoint) and analytic tools (e.g., Power BI, Tableau) is a plus.&nbsp;</li><li>Flexibility to work outside of traditional hours for meetings with global colleagues in other time zones and/or to support crisis activations.</li><li>Experience or familiarity with continuous improvement models and processes is a plus.</li><li>Understanding of basic security, risk management, crisis management, or business continuity principles is a plus.</li><li>Ability to balance multiple priorities.&nbsp;</li><li>Interest in developing in the security and risk management field.</li><li>Critical thinking skills and an innovative mindset.&nbsp;</li><li>Interest in continuous learning and skills development.</li></ul>

Role Description:The Data Engineering Senior Supervisor will lead a small team of data engineering professionals to design, build and operate high performance data centric products or solutions through the use of modern engineering practices and technologies.In this role, you will provide guidance to ensure the delivered data centric products or solutions are scalable, sustainable and robust.You will also lead team development and cross team relationships and delivery to advance the company's engineering delivery.Responsibilities:Lead a local or regional team of engineering professionals that design, develop, deploy and enhance new and existing data centric products or solutions through the use of modern platforms and technologies.Provide routine inputs and guidance to the data engineering team on business requirements analysis, technical specification's preparation, product delivery, testing and operation to support businesses strategic direction.Coach engineers, share relevant technical approaches, identify new trends, modern skills and present new methodologies within the data engineering community.Lead and develop a team, coach and make decisions related to talent management, hiring, performance, and disciplinary actions.Other duties as assignedRequirements:Minimum QualificationsBachelor's degree in a related field or equivalent experience.Minimum of four years of related work experience.Minimum of two years leading a team of Data Engineers.Preferred QualificationsConfirmed data engineering experience with data storage and management of large, heterogenous datasets, including formats, structures, and cataloging with such tools as Iceberg, Parquet, Avro, ORC, S3, HFDS, HIVE, Kudu or others.Experience leading Big Data engineering teams working in environments such as Hadoop and SparkExperience leading technology strategies with cloud Platforms including AWS, GCP or AzureExperience leading engineering teams working in streaming and stream integration or middleware platforms, tools, and architectures such as Kafka, Flink, JMS, or Kinesis.Confirmed knowledge of best practice patterns and how to apply them to modern data architectures, including data warehouses, data lakes, data mesh, hubs and associated capabilities including ingestion, governance, modeling, observability and more.Experience leveraging transformation and modeling tools, including SQL based transformation frameworks, orchestration and quality frameworks including dbt, Apache Nifi, Talend, AWS Glue, Airflow, Dagster, Great Expectations, Oozie and others.Strong programming knowledge of SQL, Python, R, Java, Scala or equivalent.Proficiency in engineering tooling including docker, git, and container orchestration services.Strong experience leading devops teams with demonstratable understanding of associated best practices for code management, continuous integration, and deployment strategies.Experience and knowledge of data governance considerations including quality, privacy, security associated implications for data product development and consumption.A passion for quality and continuous improvement with an owners mindset.Ability to work effectively as part of a team, group and cultureAbility to navigate ambiguity and work in agile ways.

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Senior Manager Data Science

Senior Data Scientist II

Senior Data Scientist

Corporate Risk Analyst

Data Engineer / Senior / Supervisor

WhiteCrow
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5 datasets Jobs found

Senior Manager Data Science

Senior Data Scientist II

Senior Data Scientist

Corporate Risk Analyst

Data Engineer / Senior / Supervisor

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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