data science engineer

Axle

<div>
 (ID: 2026-1766)
 
 &nbsp;
 
 
 
 
 Axle
 
 is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
 
 
 &nbsp;
 
 
 
 Benefits We Offer:
 
 
 <ul>
 <li>
 100% Medical, Dental &amp; Vision Coverage for Employees
 </li>
 <li>
 Paid Time Off and Paid Holidays
 </li>
 <li>
 401K match up to 5%
 </li>
 <li>
 Educational Benefits for Career Growth
 </li>
 <li>
 Employee Referral Bonus
 </li>
 <li>
 Flexible Spending Accounts:
 <ul>
 <li>
 Healthcare (FSA)
 </li>
 <li>
 Parking Reimbursement Account (PRK)
 </li>
 <li>
 Dependent Care Assistant Program (DCAP)
 </li>
 <li>
 Transportation Reimbursement Account (TRN)
 </li>
 </ul>
 </li>
 </ul>
 
 
 
 Axle is hiring a
 
 Junior Data Science Engineer
 
 to support projects across the federal space, including the National Center for Advancing Translational Sciences (NCATS) within the National Institutes of Health (NIH). You will work alongside a collaborative team of developers, data scientists, and subject matter experts to build and enhance data-driven applications, APIs, and analytics tools that support scientific research and data exploration.
 
 
 
 
 
 
 This role provides hands-on experience with modern web technologies, data pipelines, and cloud-based environments, contributing to systems that enable interactive data analysis and visualization.
 
 
 
 
 
 
 Qualifications:
 
 
 
 <ul>
 <li>
 
 
 
 Bachelor&rsquo;s Degree (or currently pursuing) in Computer Science, Data Science, Bioinformatics, Statistics, Engineering, or related field
 
 
 
 </li>
 <li>
 
 
 
 Experience or coursework in
 
 JavaScript/TypeScript and/or Python
 
 
 
 
 </li>
 <li>
 
 
 
 Exposure to
 
 full-stack development concepts
 
 (frontend and backend)
 
 
 
 </li>
 <li>
 
 
 
 Familiarity with
 
 Node.js and Angular
 
 or similar frameworks
 
 
 
 </li>
 <li>
 
 
 
 Understanding of
 
 RESTful APIs and web services
 
 
 
 
 </li>
 <li>
 
 
 
 Exposure to
 
 version control systems (Git)
 
 
 
 
 </li>
 <li>
 
 
 
 Familiarity with
 
 Agile/SCRUM development methodologies
 
 
 
 
 </li>
 <li>
 
 
 
 Basic understanding of
 
 testing frameworks and debugging practices
 
 
 
 
 </li>
 </ul>
 
 
 
 Relevant Skills:
 
 
 
 <ul>
 <li>
 
 
 
 Strong problem-solving skills and attention to detail
 
 
 
 </li>
 <li>
 
 
 
 Ability to communicate clearly and effectively (written and verbal)
 
 
 
 </li>
 <li>
 
 
 
 Ability to work both
 
 independently and in a team environment
 
 
 
 
 </li>
 <li>
 
 
 
 Adaptability in a
 
 fast-paced environment with changing priorities
 
 
 
 
 </li>
 <li>
 
 
 
 Interest in
 
 data science, analytics, or machine learning concepts
 
 
 
 
 </li>
 <li>
 
 
 
 Familiarity with
 
 data visualization or dashboarding tools
 
 is a plus
 
 
 
 </li>
 </ul>
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 
 
 
 Assist in building and maintaining
 
 data-driven applications
 
 using JavaScript/TypeScript and/or Python
 
 
 
 </li>
 <li>
 
 
 
 Support development of
 
 web applications
 
 using Node.js and Angular
 
 
 
 </li>
 <li>
 
 
 
 Contribute to the design and implementation of
 
 RESTful APIs
 
 
 
 
 </li>
 <li>
 
 
 
 Participate in
 
 testing, debugging, and enhancing existing codebases
 
 
 
 
 </li>
 <li>
 
 
 
 Help implement
 
 new features and performance improvements
 
 
 
 
 </li>
 <li>
 
 
 
 Collaborate in
 
 Agile development cycles
 
 , including sprint planning, stand-ups, and code reviews
 
 
 
 </li>
 <li>
 
 
 
 Support development of
 
 data pipelines, dashboards, and visualization tools
 
 
 
 
 </li>
 <li>
 
 
 
 Gain hands-on experience working in
 
 NIH environments across multiple sites
 
 
 
 
 </li>
 </ul>
 &nbsp;
 
 &nbsp;
 
 
 
 Disclaimer:
 
 The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
 
 
 The diversity of Axle&rsquo;s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
 
 
 Accessibility: If you need an accommodation as part of the employment process please contact:
 
 careers@axleinfo.com
 
 
 
 This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate&rsquo;s experience, qualifications, skills, and location.
 
 
 Salary Range: $80,000 USD - $90,000 USD
 
</div>

Jr. Data Science Engineer

Plymouth Rock Assurance

<div>As a Data Scientist Intern/Data Science Engineer, you will work on cutting-edge analytical and data engineering projects that drive measurable business impact across pricing, underwriting, marketing, and claims.

This internship is ideal for a technically curious, motivated problem-solver who wants hands-on data science experience.

RESPONSIBILITIES
<ul>
<li>Support the design, construction, and optimization of robust data pipelines to enable machine learning and analytical modeling.</li>
<li>Contribute to the design and implementation of data and ML workflows using orchestration tools such as Dagster, Airflow, or similar frameworks.</li>
<li>Help implement data quality checks, validation routines, and monitoring for automated data workflows.</li>
<li>Assist in organizing and managing internal GitHub repositories to standardize ML project structures and best practices.</li>
<li>Collaborate with data scientists and engineers to automate the ingestion, transformation, and delivery of data for model development.</li>
<li>Contribute to initiatives migrating analytical processes into cloud-based data lake architectures and modern platforms such as AWS or Snowflake.</li>
<li>Develop reusable and well-tested code to support analytical pipelines and internal tools using Python and SQL.</li>
<li>Conduct data mining, cleansing, and preparation tasks to build high-quality analytical datasets.</li>
<li>Participate in model development, including data profiling, model training, validation, and interpretation.</li>
<li>Build and evaluate predictive models that enhance profitability through improved segmentation and estimation of insurance risk.</li>
<li>Assist in studies evaluating new business models for customer segmentation, retention, and lifetime value.</li>
<li>Collaborate with business leaders to translate insights into operational improvements and cost efficiencies.</li>
</ul>
QUALIFICATIONS
<ul>
<li>Currently pursuing or recently completed a Master's in Data Science, Computer Science, Statistics, Economics, or related field.</li>
<li>Proficiency in Python (Pandas, NumPy, Scikit-learn, XGBoost, or PyTorch) and SQL.</li>
<li>Understanding of data engineering concepts, ETL/ELT workflows, and machine learning deployment.</li>
<li>Exposure to workflow orchestration tools (e.g., Airflow, Dagster, Prefect) and Git/GitHub for collaborative development.</li>
<li>Familiarity with Docker, CI/CD pipelines, and infrastructure-as-code tools such as Terraform preferred.</li>
<li>Knowledge of AWS cloud services such as S3, Lambda, EC2, or SageMaker a plus.</li>
<li>Experience with common modeling techniques (e.g., GLM, tree-based models, Bayesian statistics, NLP, deep learning) through coursework or projects.</li>
<li>Strong analytical, communication, and problem-solving skills.</li>
<li>A self-starter mindset, with attention to detail and enthusiasm for learning new technologies.</li>
</ul>
SALARY RANGE

The pay range for this position is $35 hourly.

ABOUT THE COMPANY

The Plymouth Rock Company and its affiliated group of companies write and manage over $2 billion in personal and commercial auto and homeowner's insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of &ldquo;A-/Excellent&rdquo;.

#LI-DNI</div>

Data Scientist Intern/Data Science Engineer

CapTech

<div>
 
 CapTech is an award-winning consulting firm that collaborates with clients to achieve what&rsquo;s possible through the power of technology. At CapTech, we&rsquo;re passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.
 
 
 
 
 
 
 
 
 
 
 Job Description
 
 
 
 
 CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.
 
 
 
 
 
 
 Specific responsibilities for the Machine Learning Engineer position include:
 
 
 
 
 
 <ul>
 <li>
 Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
 </li>
 <li>
 Deconstructing client needs into data-driven processes/models and analytical measures.
 </li>
 <li>
 Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
 </li>
 <li>
 Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
 </li>
 <li>
 Productionizing ML systems with a focus on optimization and scalability to satisfy clients&rsquo; requirements.
 </li>
 <li>
 Growing CapTech&rsquo;s Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.
 </li>
 </ul>
 
 
 
 
 
 
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree or equivalent combination of education and experience.
 </li>
 <li>
 Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
 </li>
 <li>
 Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
 </li>
 <li>
 Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
 </li>
 <li>
 Proficiency with containerization (e.g., Docker) and microservices.
 </li>
 <li>
 Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
 </li>
 <li>
 Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
 </li>
 <li>
 Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
 </li>
 <li>
 Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
 </li>
 <li>
 Knowledge of DevOps and automation best practices.
 </li>
 <li>
 Knowledge of statistics and statistical modeling methods.
 </li>
 <li>
 Knowledge of model management and model versioning best practices.
 </li>
 <li>
 Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting
 </li>
 <li>
 Experience with prompt engineering, MCP and RAG, and agentic AI architectures
 </li>
 <li>
 Strong understanding of conversational UX and prompt evaluation metrics
 </li>
 <li>
 Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
 </li>
 <li>
 Experience with multi-agent orchestration
 </li>
 </ul>
 
 
 
 
 
 
 
 
 
 
 
 Additional Information
 
 
 
 
 We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions. You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way. Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we&rsquo;ve launched extended benefits to help meet our employees&rsquo; needs.
 
 
 
 <ul>
 <li>
 CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs.
 </li>
 <li>
 Learning &amp; Development &ndash; Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
 </li>
 <li>
 Modern Health &ndash;A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life&rsquo;s ups and downs
 </li>
 <li>
 Carrot Fertility &ndash;Inclusive fertility and family-forming coverage for all paths to parenthood &ndash; including adoption, surrogacy, fertility treatments, pregnancy, and more &ndash; and opportunities for employer-sponsored funds to help pay for care
 </li>
 <li>
 Fringe &ndash;A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them &ndash; ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
 </li>
 <li>
 Employee Resource Groups &ndash; Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
 </li>
 <li>
 Philanthropic Partnerships &ndash; Opportunities to engage in partnerships and pro-bono projects that support our communities.
 </li>
 <li>
 401(k) Matching &ndash; Generous matching and no vesting period to help you continue to build financial wellness
 </li>
 </ul>
 
 CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness &mdash; each foundational to our core values. We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE. As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email lmassa@captechconsulting.com.
 
 
 
 
 At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.
 
</div>

Machine Learning / Data Science Engineer

Mindrift

<div>
 
 Please submit your CV in English and indicate your level of English proficiency.
 
 
 
 Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.
 
 Participation is project-based, not permanent employment.
 
 
 
 
 What This Opportunity Involves
 
 
 
 While each project involves unique tasks, contributors may:
 
 
 <ul>
 <li>
 Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare)
 </li>
 <li>
 Create problems requiring Python programming to solve (using Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, Seaborn)
 </li>
 <li>
 Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
 </li>
 <li>
 Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction
 </li>
 <li>
 Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility
 </li>
 <li>
 Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency
 </li>
 <li>
 Design end-to-end problems spanning the complete data science pipeline (data ingestion &rarr; cleaning &rarr; EDA &rarr; modeling &rarr; validation &rarr; deployment considerations)
 </li>
 <li>
 Incorporate big data processing scenarios requiring scalable computational approaches
 </li>
 <li>
 Verify solutions using Python with standard data science libraries and statistical methods
 </li>
 <li>
 Document problem statements clearly with realistic business contexts and provide verified correct answers
 
 
 </li>
 </ul>
 
 What We Look For
 
 
 
 This opportunity is a good fit for Data Science specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:
 
 
 <ul>
 <li>
 5+ years of hands-on data science experience with proven business impact
 </li>
 <li>
 Portfolio of completed projects and publications showcasing real-world problem-solving
 </li>
 <li>
 Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels)
 </li>
 <li>
 Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications
 </li>
 <li>
 Expert with SQL and database operations for data manipulation and analysis
 </li>
 <li>
 Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)
 </li>
 <li>
 Understanding of MLOps practices and model deployment workflows
 </li>
 <li>
 Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)
 </li>
 <li>
 Strong written English (C1+)
 
 
 </li>
 </ul>
 
 How It Works
 
 
 
 Apply &rarr; Pass qualification(s) &rarr; Join a project &rarr; Complete tasks &rarr; Get paid
 
 
 
 Project time expectations
 
 
 
 For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.
 
 
 
 Compensation
 
 
 
 On this project, contributors can earn up to
 
 $90 per hour equivalent
 
 , depending on their level and pace of contribution.
 
 
 Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.
</div>

Freelance Data Science Engineer (Python & SQL)

Apple

As part of the work on machine-generated dialog we are developing novel measurements of its quality. These include cutting-edge llm-judges for aspects like groundedness (lack of hallucinations), Siri Tone and Style (a suite of Design requirements), Safety, and others. 
 
Description 
 
To measure our progress on this front, we need to track the state of our dataset composition, accuracy of llm-judges, human expert review results in a central and visual representation. A DRI for Metrics and Reporting will:&quot;,&quot;responsibilities&quot;:&quot;Build an easy to use dashboard for our datasets - requires integration with other teams 
 
Build dashboards to visualize our status 
 
Help define useful metrics 
 
Build tools to facilitate processing of human review results (inter-annotator agreement, storage, selection of the most useful data points for human expert review) 
 
Build tools and pipelines to streamline quality measurement processes 
 
Preferred Qualifications 
 
Experience with writing and architecting production level code 
 
Deep understanding of Machine Learning concepts 
 
Experience in Model training and/or evaluation 
 
Good engineering practices to create sustainable and easy to use metric reporting pipelines 
 
Attunement to computational linguistics, language quality is a plus 
 
Minimum Qualifications 
 
M.S. or Ph.D. in Computer Science, Data Science, Data Engineering 
 
3+ years in data-science and/or data-engineering (iceberg, pandas python, Tableau or equivalent, data collection and visualization) 
 
2+ years of python coding 
 
Good understanding of metrics, crowd science, annotation analysis, statistics 
 
Ability to work independently and cross-functionally to integrate in partner team reporting systems and pipelines 
 
Excellent communication skills and the ability to thrive in a highly collaborative work environment 
 
Good engineering practices to create sustainable and easy to use metric reporting pipelines 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Sr. Data Science Engineer, Siri Core Modeling

Arrow Electronics

<div>
 
 Position
 
 
 
 Data Scientist / Senior Machine Learning Engineer
 
 
 
 Job Description
 
 
 
 
 Position Overview:
 
 
 
 As Data Scientist / Senior Machine Learning Engineer at Arrow Electronics, you will assume a pivotal role in driving our data science and machine learning initiatives to reach unprecedented heights. Collaborating closely with cross-functional multinational teams, your responsibilities will encompass the end-to-end machine learning lifecycle, including stakeholder communications, data analysis, designing, development, deployment, and optimization of cutting-edge models aimed at addressing intricate challenges and generating actionable insights. Your expertise in data analysis, model development, and deployment will be crucial in shaping the future of our company.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms to solve real-world problems in various domains.
 </li>
 <li>
 Data Analysis: Explore and analyze large datasets to extract meaningful insights and identify trends, anomalies, and patterns.
 </li>
 <li>
 Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics and fine-tune models for optimal results.
 </li>
 <li>
 Deployment: Lead the deployment of machine learning models into production environments and ensure scalability and efficiency.
 </li>
 <li>
 Cross-functional Collaboration: Collaborate closely with business stakeholders, software engineers, data engineers, and domain experts to integrate machine learning solutions into our products and services.
 </li>
 <li>
 Mentorship: Provide guidance and mentorship to junior data scientists and machine learning engineers, fostering a culture of continuous learning and growth.
 </li>
 <li>
 Research and Innovation: Stay up-to-date with the latest advancements in the field of data science and machine learning and apply innovative techniques to solve complex challenges.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Proven experience (2 to 5 years) in developing and deploying machine learning models in a production environment.
 </li>
 <li>
 Proficiency in programming languages, especially Python, and experience with data-related libraries such as pandas, matplotlib, NumPy, etc.
 </li>
 <li>
 Strong knowledge of machine learning frameworks and libraries.
 </li>
 <li>
 Expertise in data preprocessing, feature engineering, and model selection.
 </li>
 <li>
 Familiarity with large language models and AI agent design.
 </li>
 <li>
 Experience with text-based NLP, information extraction, entity recognition, and text-related data science tasks is highly desirable.
 </li>
 <li>
 Strong communication skills and the ability to convey technical concepts to non-technical stakeholders.
 </li>
 <li>
 Experience with vectorized databases and unstructured search engines is a plus.
 </li>
 <li>
 A Master&rsquo;s degree in computer science, Statistics, Data Science, or a related field is a plus.
 </li>
 <li>
 Publications or contributions to open-source projects are a plus.
 
 
 </li>
 </ul>
 If you are a passionate and experienced Data Scientist / Senior Machine Learning Engineer who thrives on solving challenging problems and wants to make a significant impact in the field, we encourage you to apply and join our dynamic team at Arrow Electronics Together, we will drive innovation and shape the future of data science and machine learning.
 
 
 
 Location:
 
 
 
 EG-Cairo, Egypt (Al Emdad &amp; Al Tamween)
 
 
 
 Time Type
 
 
 
 Full time
 
 
 
 Job Category
 
 
 
 Information Technology
</div>

Data Scientist / Senior Machine Learning Engineer

Walmart

<div><h2 class="jobSectionHeader">Position Summary...</h2><h2 class="jobSectionHeader">
What you'll do...</h2>
Position Summary...
The Catalog Data Science team at Walmart plays a pivotal role in maintaining and enhancing the data quality of Walmart's massive catalog. We aid supplier onboarding, merchandise acquisition, inventory management, and shopper experience by leveraging cutting-edge technologies in GenAI, Machine Learning, Deep Learning, and Engineering. We tackle complex problems spanning natural language understanding, image classification, and recommendation to outlier detection, visualization, and model serving. We take pride in writing solid production code in Python, deploying and supporting model services and pipelines, and pushing the boundaries in latency, throughput, and scalability.
Trust and Safety (T&amp;S) is an integral part of the Catalog Data Science Org, responsible for maintaining customer trust in the Walmart marketplace. We employ state-of-the-art GenAI and ML models to identify products that violate Walmart's marketplace policies. Our end-to-end ML pipelines are designed to scale and detect policy violations across hundreds of violation classes and billions of catalog items &mdash; ensuring a safe marketplace for our customers. Our work carries high visibility, directly impacting marketplace growth and compliance at Walmart.
As a Senior Data Scientist (Machine Learning Engineer) on the Trust and Safety team, you will collaborate with other Data Scientists and ML Engineers to develop, deploy, and scale machine learning models in production. You will play a key role in building the next generation of our compliance detection platform &mdash; driving model serving, pipeline reliability, and the adoption of GenAI-powered solutions to more accurately detect items that violate compliance policies.
What you'll do&hellip;<ul><li>
Design and deploy production-grade ML systems for Walmart's Catalog Trust &amp; Safety platform &mdash; spanning classification, detection, and segmentation</li><li>
Apply GenAI, NLP, and Computer Vision techniques to build and continuously improve models for compliance detection, content moderation, and policy violation classification</li><li>
Own the full model lifecycle &mdash; from experimentation and offline evaluation through serving, monitoring, and iterative improvement in production</li><li>
Build and optimize high-throughput batch and real-time inference pipelines using frameworks like Ray, Triton, and vLLM, with a focus on latency, cost, and reliability</li><li>
Drive ML architecture decisions &mdash; including model selection, distillation, quantization, and serving strategies</li><li>
Partner with Compliance, Product, and Operations teams to translate business requirements into model KPIs, evaluation frameworks, and measurable impact</li><li>
Establish and enforce ML engineering best practices across the team: reproducible training, robust evaluation datasets, versioned artifacts, and production readiness standards</li><li>
Contribute to the broader ML engineering community at Walmart through technical documentation, internal talks, and cross-team knowledge sharing</li></ul>
What you'll bring&hellip;<ul><li>
PhD or Master's in Computer Science, or equivalent experience; 3+ years building and deploying production ML systems at scale</li><li>
Deep expertise in model serving and inference optimization &mdash; experience with Triton Inference Server, vLLM, TorchServe, or comparable frameworks</li><li>
Hands-on experience with Generative AI technologies: LLMs, multimodal models, RAG architectures, prompt engineering, and fine-tuning (LoRA/QLoRA, PEFT)</li><li>
Strong foundation in classical ML, deep learning, and modern architectures &mdash; CNNs, Transformers, and domain-specific variants</li><li>
Proven ability to build and operate large-scale batch and real-time inference pipelines handling high QPS with strict latency and throughput SLAs</li><li>
Proficiency in Python and ML ecosystem tooling &mdash; PyTorch, HuggingFace, scikit-learn, NumPy; familiarity with distributed compute frameworks (Ray, Spark)</li><li>
Experience deploying and managing ML workloads on Kubernetes; solid working knowledge of Docker, Helm, and container orchestration</li><li>
Familiarity with ML observability &mdash; model monitoring, data drift detection, performance degradation alerting, and online evaluation strategies</li><li>
Practical experience with MLOps tooling: experiment tracking (MLflow, W&amp;B), pipeline orchestration (Airflow, Kubeflow), and CI/CD for ML</li><li>
Hands-on with at least one major cloud platform (GCP, Azure etc.) and comfort with managed ML services and GPU infrastructure</li><li>
Working knowledge of relational and NoSQL databases</li><li>
Experience with vector databases (Pinecone, Weaviate, pgvector) and hybrid retrieval systems for GenAI applications</li><li>
Experience with Version Control Systems, especially Git</li><li>
Strong verbal and written communication skills; ability to translate complex ML systems into clear technical and business narratives</li><li>
Proactive in tracking the latest AI/ML research and translating advancements into production-grade solutions</li></ul>
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&lrm;<h2 class="jobSectionHeader">
Minimum Qualifications...</h2>
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1- Bachelor&rsquo;s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years' experience in an analytics related field. Option 2- Master&rsquo;s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years' experience in an analytics related field. Option 3 - 5 years' experience in an analytics or related field.<h2 class="jobSectionHeader">
Preferred Qualifications...</h2>
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
Data science, machine learning, optimization models, Master&rsquo;s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart&rsquo;s accessibility standards and guidelines for supporting an inclusive culture.<h2 class="jobSectionHeader">
Primary Location...</h2>
1375 Crossman Ave, Sunnyvale, CA 94089-1114, United States of America
Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.</div>

Senior, Data Scientist (Machine Learning Engineer)

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