Data Scientist II Job at Arrive Logistics (Chicago)

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Data Scientist II

Arrive Logistics is a leading transportation and technology company in North Ame...

Location

United States , Austin

Salary:

Not provided

Arrive Logistics

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in a quantitative field (computer science, statistics, linguistics, or related) and 2–4 years of applied ML or data science experience, or equivalent practical experience
Hands-on experience building or improving NLP or LLM-based systems in applied settings
Familiarity with text classification, information extraction, or other NLP tasks — and an understanding of where these systems fail
Experience with both prompt engineering and fine-tuning approaches for language tasks, with the judgment to know when to apply each
Familiarity with modern retrieval strategies and RAG architectures and how they affect LLM system performance
Experience with Hugging Face Transformers for text classification or related NLP tasks
Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including comfort with statistical methods for measuring model performance
Proficiency in Python and SQL, and comfort working with structured and unstructured data
Ability to operate effectively in ambiguous problem spaces — scoping technical approaches when requirements are not fully defined
Strong written communication skills

Job Responsibility

Develop, evaluate, and iterate on NLP and LLM-based systems, including text classification, information extraction, and context retrieval pipelines
Build measurement and evaluation frameworks — both offline and online — to assess where and why systems are underperforming and quantify the impact of improvements
Develop golden test datasets and define methodologies for creating and maintaining them over time, including designing annotation guidelines and ensuring label quality
Evaluate and apply the appropriate approach for language tasks — whether prompt engineering, fine-tuning, or classical NLP methods — including modern retrieval and RAG architectures and LLM evaluation methodologies, based on the problem and available data
Perform structured analysis of system performance to surface failure modes, data gaps, and high-value areas for investment, applying sound statistical reasoning to evaluation results
Partner with engineers to support deployment, integration, and monitoring of ML and AI systems in production
Contribute to standards and best practices around deploying, evaluating, and monitoring text and language-based ML systems
Document work clearly and maintain knowledge artifacts that make systems understandable and maintainable over time
Collaborate with senior data scientists and cross-functional partners to translate business needs into well-scoped technical solutions, including communicating findings and recommendations to non-technical stakeholders

What we offer

Comprehensive benefits package, including medical, dental, vision, life, disability, and supplemental coverage
Matching 401(k) program
Employee Resource Groups
Office wide engagement activities, team events, happy hours and more
Casual dress code
Work in the booming city of Austin, TX – we are in a convenient location close to the airport and downtown
Free on-site parking
Fully stocked coffee bar, Broker’s Brew
Onsite gym
Free counseling sessions through our Employee Assistance Program

Fulltime

Data Scientist II

Are you excited by the opportunity to use machine learning, NLP, and generative ...

Location

United Kingdom , London

Salary:

Not provided

myGwork - LGBTQ+ Business Community

Expiration Date

Until further notice

Requirements

Experience in data science, machine learning, artificial intelligence, NLP, statistics, applied mathematics, computer science, or a related quantitative area
Experience working with frontier LLMs such as OpenAI's GPTs, Anthropic's Claude, and Google's Gemini, including fine-tuning LLMs and/or SLMs
Strong Python skills and a habit of writing clean, maintainable, well-tested code
A solid grasp of machine learning fundamentals, including supervised and unsupervised learning, feature engineering, model evaluation, model selection, and performance measurement
Experience working with structured, semi-structured, or unstructured data, especially large-scale text or content datasets
Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib
The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem-solving skills, and attention to quality
Clear communication skills, a collaborative approach to working with engineering, product, and business stakeholders, and a genuine interest in building production-ready systems that deliver real user value

Job Responsibility

Design and build machine learning, NLP, and generative AI systems for scientific discovery, knowledge extraction, decision support, and intelligent content understanding
Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline
Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI
Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence-grounded generation
Build, evaluate, fine-tune, prompt, and integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value
Write clean, tested, production-quality Python and contribute reusable data science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement
Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems
Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences

What we offer

healthy work/life balance
wellbeing initiatives
shared parental leave
study assistance
sabbaticals
flexible working hours

Fulltime

Data Scientist II

AIII (AI Innovation & Incubation) Silicon Valley is a team of applied research s...

Location

United States , Santa Clara

Salary:

122500.00 - 161175.00 USD / Year

Ericsson

Expiration Date

Until further notice

Requirements

MS in Computer Science or a closely related field with strong foundations in machine learning
1–4 years of experience (industry and/or research) working with deep neural networks, ideally including large‑scale or LLM‑based models
Strong Python programming skills and experience with modern ML frameworks (e.g., PyTorch, JAX)
Proven ability to read and understand research papers and implement or reproduce the described methods
Experience working with at least one cloud platform (GCP, AWS, or Azure)
Comfort working in a rapidly changing AI environment, handling uncertainty, and continuously upskilling
Clear communication and collaborative mindset in a professional team setting

Job Responsibility

Design, train, and evaluate deep neural networks, including LLMs and other foundation models, for telco‑relevant use cases
Prototype AI agents and solution pipelines that use LLMs/LVMs and modern ML techniques to improve network performance and operations
Translate research into code by reading top‑tier conference papers (e.g., CVPR, NeurIPS, ICML, ICLR) and reproducing key ideas in experiments
Run experiments on cloud platforms (e.g., GCP, AWS, Azure) or on-prem GPU clusters as part of scalable training and evaluation workflows
Collaborate with applied researchers, engineers, and domain experts to turn PoCs into solutions that can be productized
Stay current with the fast‑moving AI landscape, evaluating new methods and tools and suggesting how we can apply them in our work

What we offer

Short-Term Variable Compensation Plan (annual bonus)
Choice of three medical plan options and a dental plan option
Company credits for medical and dental premiums
Ericsson US 401(k) Plan with automatic 3% company contribution and matching contributions up to 4%
Company credits for basic life insurance, basic accidental death and dismemberment coverage, short-term and long-term disability coverage
Stock Purchase Plan
Minimum of 15 days of accrued vacation
Up to 3 personal days per year
11 annual holidays
8 hours of volunteer time

Fulltime

Data Scientist II

The Windows and Devices mission is to build innovative, trusted, and open produc...

Location

India , Hyderabad

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience

Job Responsibility

Work with business stakeholders, Solution Managers, TPMs, and engineering teams to understand business context and translate defined problems into analytical and technical approaches
Contribute to scoping discussions, surfacing trade-offs and helping refine the path from business need to AI solution
Build and deploy production AI/ML systems (ML/DL, GenAI, optimization) using Azure AI, open-source frameworks, and custom models, with ownership of model development from prototype through deployment
Apply engineering best practices for code quality, MLOps, testing, and monitoring
contribute to improving team-wide standards
Stay current with emerging AI tools and frameworks
evaluate and apply them to your work
Share learnings with the team
collaborate openly and contribute to a rigorous, inclusive engineering culture

Fulltime

Data Scientist II

We’re looking for a knowledgeable Data Scientist - Product Analytics to support ...

Location

Canada

Salary:

113600.00 - 142000.00 CAD / Year

Coursera

Expiration Date

Until further notice

Requirements

Background in economics, statistics, data science, computer science, or a related technical field
3+ years of experience as a data scientist, data analyst, or business intelligence analyst
Strong SQL skills and proficiency with at least one scripting language (e.g. Python, R)
Proficiency in BI tools (e.g. Sigma, Databricks, Looker, Tableau)
Excellent communication skills, with the ability to translate complex data findings into actionable insights
Strong attention to detail and the ability to manage multiple projects simultaneously

Job Responsibility

Develop an understanding of Coursera’s products, business, and learners to tie insights and analysis to actionable recommendations
Analyze the results of A/B tests and conduct deep dives on our learner and product experiences
Create dashboards and set up systems and tools for tracking product metrics
Create leverage by enabling Product Managers to better self-serve data on their product area
Present findings and recommendations to product teams and cross-functional partners in a clear and concise manner

What we offer

bonus
equity
benefits

Fulltime

Data Scientist II

At Seismic, we believe that AI, particularly Generative AI, will empower and tra...

Location

United States; Canada , Remote; Toronto

Salary:

78600.00 - 135600.00 USD / Year

Seismic

Expiration Date

Until further notice

Requirements

Bachelor’s, Master’s, or higher degree in Computer Science, Engineering, or related fields
2–4 years of industry experience in data science, machine learning, or applied AI (or 1–2 years with an advanced degree), with experience contributing to production systems or product features
Strong knowledge of Python is a must
Ideally comfortable with LangChain, pandas and other GenAI related python libraries
Strong hands-on skills in AI & ML service development, end-to-end product engineering, and data analytics
Experience with GenAI and cloud technologies
Ability to translate business and customer problems into technical solutions, and to iterate based on user feedback and data
Exceptional communication skills, with the ability to collaborate with cross-functional teams
Strong problem-solving and decision-making abilities, with a strategic mindset and a passion for driving product vision and business outcomes through technology
Experience thriving in dynamic, fast-paced environments, preferably within SaaS or technology-driven companies focused on customer and product innovation

Job Responsibility

Contribute to the development of AI-powered product features, from prototyping and experimentation through production delivery, deployment and iteration
Build and improve AI/machine learning, especially LLM-based systems (e.g., copilots, conversational workflows, or agent-style experiences) using established frameworks and internal platforms
Work with product and design teams to understand user needs and translate them into practical AI-driven solutions
Partner with engineers, designers, and other data scientists to build, test, and refine AI features, balancing model performance, system reliability, and user experience
Help define and analyze metrics to evaluate model performance, product usage, and customer impact, and use data to guide improvements

Fulltime

Data Scientist II

The Copilot and Platform Ecosystem (CAPE) team at Microsoft is on a mission to d...

Location

United States , Redmond

Salary:

100600.00 - 199000.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements
This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter

Job Responsibility

Partner with data engineering, product management, and engineering to define analytical questions, success metrics, and hypotheses that drive Copilot business outcomes
Analyze large-scale product and customer telemetry (e.g., Kusto/ADX, Cosmos, logs, usage signals) to deliver clear, actionable insights for leaders and partner teams
Design and interpret experiments and evaluations (A/B tests, cohort/retention analysis, causal methods as appropriate) to measure impact of features, agents, and platform changes
Own and evolve core metrics and definitions (engagement, retention, adoption, quality), ensuring consistency and trust across reporting and dashboards
Improve data quality, freshness, and correctness by identifying gaps/anomalies and strengthening signal pipelines in partnership with data engineering
Build analytical models or lightweight ML to support forecasting, segmentation, classification, and outcome measurement as needed
Communicate complex analyses as concise narratives for technical and non-technical audiences
contribute to documentation and analytics best practices across CAPE

Fulltime

Data Scientist II

Security is one of the most critical priorities for our customers in a world cha...

Location

India , Bangalore

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

5+ years of programming language experience like C/C++/C/Python required and hands on experience in using technologies such as Spark, Azure ML, SQL, KQL, Databricks, etc.
Able to prepare data pipelines and feature engineering pipelines to build robust models using SQL, PySpark, Azure Data Studio etc.
Knowledge of Classification, Prediction, Anomaly Detection, Optimization, Graph ML, NLP
Candidate must be comfortable in manipulating and analyzing complex, high dimensional data from various sources to solve difficult problems
Knowledge of working in cloud-computing environment like Azure / AWS / Google Cloud
Proficient in Relational Databases (SQL), Big Data Technologies (PySpark). Azure storage technologies such as ADLS, cosmos DB, etc.
Bachelor's or higher degrees in Computer Science, Statistics, Mathematics, Engineering, or related disciplines

Job Responsibility

Build algorithms and innovative methods to discover and defend real world sophisticated cloud-based attacks in SaaS ecosystem
Collaborate with other data scientists to develop machine learning systems for detecting anomalies, compromises, fraud, and non-human identity cyber-attacks using both Gen AI and graph-based systems
Identify, integrate multiple data sources, or types of data, and develop expertise with multiple data sources to tell a story, identify new patterns and business opportunities, and communicate visually and verbally with clear and compelling data-driven stories
Analyze extensive datasets and develop a robust, scalable feature engineering pipeline within a PySpark-based environment
Acquires and uses broad knowledge of innovative methods, algorithms, and tools from within Microsoft and from the scientific literature and applies his or her own analysis of scalability and applicability to the formulated problem
Work across Threat Researchers, engineering, and product teams to enable metrics for product success
Contribute to active engagement with the security ecosystem through Research papers, presentations, and blogs
Provide subject matter expertise to customers based on industry attack trends and product capabilities

Fulltime

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