senior software engineer analytics

Openkyber

<div>Position Title: Senior Analytics Engineer
Location: Remote
Position Overview
We are seeking a Senior Analytics Engineer to support the modernization of analytics and reporting workflows within a Business Informatics organization. This role focuses on translating and enhancing legacy SAS-based analytics into scalable, maintainable Python-based solutions. This is not a pure software engineering role and not a traditional reporting analyst role. The ideal candidate combines strong analytical thinking, deep Python expertise, and the ability to interpret and refactor complex SAS logic while preserving business intent and output accuracy.
Key Responsibilities
<ul><li>Analyze and interpret existing SAS programs, including DATA steps, PROC SQL, and analytical procedures</li>
<li>Translate SAS-based analytics and transformations into Python using pandas, numpy, and SQL while preserving business logic</li>
<li>Partner closely with Business Informatics stakeholders to understand reporting intent, metrics, and downstream usage</li>
<li>Validate converted logic by reconciling outputs, row counts, and aggregations between SAS and Python</li>
<li>Improve and modernize analytics pipelines by simplifying logic and reducing technical debt</li>
<li>Collaborate with technology and data platform teams to ensure Python solutions align with enterprise standards</li>
<li>Document business logic, assumptions, and data transformations for long-term maintainability</li>
<li>Ensure accuracy and integrity of analytical outputs through thorough validation and testing</li>
</ul>Required Qualifications
<ul><li>Strong experience with Python for data analysis, including pandas, numpy, and SQL integration</li>
<li>Working knowledge of SAS, with the ability to confidently read and interpret existing SAS code</li>
<li>Experience translating or modernizing legacy analytics or reporting logic</li>
<li>Solid understanding of analytics concepts such as aggregations, joins, time-based logic, and derived metrics</li>
<li>Experience validating analytical outputs and ensuring data accuracy</li>
<li>Ability to collaborate with business users and translate analytical requirements into technical solutions</li>
</ul>Preferred Qualifications
<ul><li>Experience in healthcare, payer, or regulated data environments</li>
<li>Familiarity with SAS macros and common PROC workflows</li>
<li>Exposure to cloud-based analytics platforms or modern data stacks</li>
<li>Experience supporting Business Intelligence, reporting, or informatics teams</li>
<li>Background in analytics engineering or data transformation roles
</li></ul>For applications and inquiries, contact: hirings@openkyber.com</div>

OCI Analytics Cloud Engineer

Apple

Would you like to be a part of Apple&rsquo;s AI and Machine Learning org, where we encourage and create groundbreaking technology for multi-modal models with strong agent and reasoning capabilities? The Data and Machine Learning Innovation (DMLI) team is seeking a passionate Machine Learning Engineer to explore new methods, challenge existing metrics and protocols, and develop new insightful practices for real-world ML challenges. As a team member, you will work on some of the most ambitious technical challenges in the field. Your role will involve collaborating closely with our team of machine learning researchers, engineers, and data scientists. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to build for billions of users worldwide. 
 
Description 
 
As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying innovative research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline-from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem. 
 
Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. 
 
YOUR WORK MAY SPAN VARIOUS APPLICATIONS, INCLUDING: 
 
Designing self-supervised and semi-supervised representation learning pipelines, and fine-tuning strategies for tasks like speech recognition and speaker identification. 
 
Applying data selection techniques such as novelty detection and active learning across multi modalities to improve data efficiency and reduce distributional gaps. 
 
Modeling data distributions using ML/statistical methods to uncover patterns, reduce redundancy, and handle out-of-distribution challenges. 
 
Rapidly learning new methods and domains as needed, and guiding product teams in selecting effective ML solutions. 
 
Preferred Qualifications 
 
Deep understanding of multi-modal foundation models. 
 
Staying up-to-date with emerging trends in generative AI and multi-modal LLMs. 
 
The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively with multi-functional teams. 
 
Demonstrated publication records in relevant conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.). 
 
Track records of adopting ML to solve cross-disciplinary problems. 
 
Minimum Qualifications 
 
Deep technical skills in one or more machine learning areas, such as computer vision, audio, combinatorial optimization, causality analysis, natural language processing, and deep learning. 
 
Strong software development skills with proficiency in Python; hands-on experience working with deep learning toolkits like PyTorch, TensorFlow, or JAX (one of). 
 
5+ years of experience developing and evaluating ML applications, demonstrating a passion for understanding and improving model/data quality.&lsquo; 
 
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 $147,400 and $272,100, 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.

AIML - Sr Machine Learning Engineer - Data and ML Innovation

<div>Do you want to play a part in the next revolution in Foundation Models? Contribute to model hillclimbing for Apple Intelligence features that leverage Apple Foundation Models, and work with the people who built the intelligent products that helps millions of people get things done - just by asking or typing? 
 
The vision for the AI/ML FM Data organization is to improve Foundation Models by leveraging data from a variety of sources: crawl, license, vendor and internal crowd-sourcing. As a Sr Software Engineering on the team, you will drive backend innovations, identify key opportunity areas where data can play a crucial role and experiment with various data augmentation strategies to improve model training efficiency and performance.. 
 
Description 
 
We are looking for people with a track record in building scalable pipelines and services. Join us, and impact hundreds of millions of customers across billions of their interactions with foundation model powered Apple Intelligence features, that are available on iPhone, iPad, HomePod, Mac, Watch, CarPlay, and tv across more than 30 languages! 
 
As a Sr Backend Software engineer, you will be responsible for the following areas. 
 
<ul><li>Training data pipeline development. Convert raw data into format acceptable by training jobs on GCP and AWS. Leverage internal and open-sourced training modules.</li></ul> 
<ul><li>Large scale inferences: Leverage internal and open-sourced inference stack to generate inferences with fine-tuned LLMs on massive amounts of data, for pre-train and post-training</li></ul> 
<ul><li>Data processing and data filtering: Have the ability to efficiently process and filter very large amounts of data, often times messy.</li></ul> 
<ul><li>Scalable web services backend and APIs to support data access and data inspection tools</li></ul> 

Preferred Qualifications 
 
Familiarity with streaming-processing (Kafka). Familiarity with a variety of build tools (Jenkins, Maven, Docker, Gradle). 
 
Experience providing architecture and design guidance. 
 
A good communicator with clear and concise, active listening and empathy skills. 
 
Are self-motivated and curious. Strive to continually learn on the job. 
 
Have demonstrated creative and critical thinking with an innate drive to improve how things work. Have a high tolerance for ambiguity. 
 
Minimum Qualifications 
 
BS in Computer Science or Equivalent. 
 
10+ years of programming experience in Python. Extensive experiences in concurrency and parallelism, functional programming, decorators. Familiarity in other programming languages (Java/GoLang/Rust/Swift). 
 
Proficient in REST API, Redis, VectorDB or other large scale data storage systems. 
 
Solid foundational programming skills (algorithms, data structures, OOP, etc). 
 
Experience designing, writing, reviewing, testing and delivering software for applications and systems at scale. 
 
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 $139,500 and $258,100, 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.</div>

AIML - Sr Backend Engineer, Data and ML Innovation

The Home Depot

<div>Position Purpose:
The Sr. Manager Decision Analytics position leads the Insights and Reporting functions for Store Operations and Services divisions. This role works closely with the Director within Decision Analytics in defining the analytical strategy and approach for projects and processes and effectively manage talent. The role works cross-functionally with business partners from across Store Operations, Services, Product and IT to design and implement decision analytics, tools, and new visibility/reporting capabilities. This role has responsibility for creating analytics, translating business questions to actionable insights, supporting ongoing analytical needs, designing analytical and reporting platforms, and partnering with cross-functional teams to deliver high quality analytics solutions for The Home Depot. These responsibilities require effective communication skills, building relationships and partnerships, and leveraging business proficiency for solutions and recommendations. 
Key Responsibilities:<ul><li>
60% Collaborate with stakeholders, business partners, colleagues, developers, and business analysts to deliver high quality analytics solutions</li><li>
25% Data analytics with large volumes of data, using a wide variety of database applications / analytical tools including SQL, SAS, R, and python</li><li>
5% Data cleansing, validation, testing</li><li>
5% Enhancements / modifications to systems &amp; procedures</li><li>
5% Supporting end users, problem solving, troubleshooting</li></ul> 
Direct Manager/Direct Reports:<ul><li>
Reports to a Director.</li><li>
This position has 2-3 direct reports.</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel less than 10% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
Master's degree in Analytics, Finance, or Information Systems or related field is preferred</li><li>
Eight or more years of experience in analytics or business intelligence is preferred</li><li>
Experience in SQL, SAS, Tableau, R, python and similar tools preferred</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
6</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
None</li></ul></div>

Senior Manager Decision Analytics - Insights & Reporting

Are you excited about using data to shape the experience of products used by hundreds of millions of people around the world? 
 
The Evaluation Data Engineering team, part of Apple&rsquo;s SWE organization, builds the scalable and reliable data platform that powers Siri, Search, and Machine Learning across Apple. 
 
We&rsquo;re looking for collaborative and mission-driven software engineers who care deeply about data quality, user impact, and building at scale. 
 
If you&rsquo;re passionate about tackling complex data challenges, eager to work with petabytes of data, and inspired by Apple&rsquo;s commitment to privacy and innovation, we&rsquo;d love to hear from you. 
 
Description 
 
In this role, you&rsquo;ll work cross-functionally across product and data science teams to build large-scale stream and batch processing data pipelines that power Analytics, Experimentation, and Machine Learning. 
 
You will design a unified and groundbreaking data processing framework using Flink, and/or Spark. 
 
Your work will focus on optimizing performance, ensuring data quality, and contributing to a long-term vision that extends the framework&rsquo;s capabilities to new user scenarios and groundbreaking machine learning applications. 
 
You will collaborate closely with Siri, Search, and other teams to design solutions that transform raw data into datasets that drive innovation. 
 
You&rsquo;ll automate dataset lifecycles with strong quality standards and help partners confidently use the data for product insights. 
 
Preferred Qualifications 
 
Strong in algorithms, data structures, data modeling, and SQL, with experience working on large-scale, complex, and high-dimensional datasets. 
 
Experience with machine learning algorithms or pipelines, particularly in the context of data engineering. 
 
Experience supporting ML engineers or data scientists with feature engineering or model data pipelines is a plus. 
 
Familiarity with testing tools and methodologies for validating large-scale, distributed data systems (e.g., data quality checks, pipeline testing frameworks, fault tolerance testing). 
 
Proven software engineering fundamentals, including experience with design, testing, version control, and CI/CD best practices. 
 
Comfortable working independently in a fast-paced, ambiguous environment. 
 
Excellent communication and problem-solving skills. 
 
Minimum Qualifications 
 
7+ years of experience designing, building, and maintaining distributed data processing systems at scale. 
 
5+ years of hands-on experience with stream and/or batch processing technologies such as Flink, Spark, Kafka, Airflow, Iceberg, and Trino. 
 
2-3 years of experience in full-stack development 
 
Proficient in at least one modern programming language (e.g., Java, Scala, and Python). 
 
MS or BS in Computer Science, Engineering, Math, Statistics, or a related field, or equivalent practical experience in data engineering. 
 
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.

AIML - Sr Software Data Engineer, Evaluation

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
AWS's Trainium and Inferentia chips power the world's largest machine learning clusters. Our team builds C++ models of these custom SoCs that RTL designers, verification engineers, and software teams depend on throughout the silicon development lifecycle. We're looking for a modeling engineer to build and own models that directly impact how our chips are designed, verified, and brought to production. 
 
What you'll do: 
 
<ul><li>Build and own models of SoC subsystems &mdash; translating architecture specs and RTL behavior into accurate, testable C++ models</li><li>Work directly with RTL design and verification teams to validate model behavior against RTL, debug discrepancies, and support pre-silicon verification flows</li><li>Develop model-based test infrastructure: regression suites, RTL correlation checks, and coverage-driven testing</li><li>Contribute to performance modeling efforts &mdash; building cycle-approximate models that help architects evaluate design trade-offs before RTL exists</li><li>Improve modeling methodology and infrastructure: how models are structured, integrated, tested, and released to DV and architecture teams</li><li>Collaborate with chip architects to understand upcoming designs and plan modeling work ahead of RTL availability</li></ul> 
Why this role is interesting: 
 
<ul><li>Your models are used to verify silicon before it's built &mdash; bugs you catch save months of schedule and millions of dollars</li><li>You'll work at the intersection of software engineering and chip design, with deep visibility into how custom ML accelerators are architected</li><li>As the team scales, there's a clear path into architectural modeling &mdash; using your models to influence chip design decisions, not just validate them</li><li>Small team, high ownership, direct impact on AWS's most strategic silicon programs</li></ul> 
You will thrive in this role if you: 
 
<ul><li>Have built functional or performance models of SoCs, ASICs, GPUs, CPUs, or IP blocks</li><li>Are comfortable working with architectural / design specifications or reference implementations and translating them into C++ or SystemC models</li><li>Understand verification concepts and have worked with DV teams or in pre-silicon validation environments</li><li>Care about model fidelity and have experience correlating models against RTL or silicon</li><li>Are interested in expanding into architectural performance modeling as the team grows</li><li>Enjoy working on a small, high-impact team where you own significant pieces of the stack</li></ul> 
No ML background needed. You'll learn the ML accelerator domain on the job. 
 
This role can be based in Cupertino, CA or Austin, TX.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Experience programming languages such as C/C++, Python, Java or Perl</li><li>2+ years writing functional or performance models of hardware (SoCs, ASICs, GPUs, CPUs, IP blocks)</li><li>Familiarity with SoC, CPU, GPU, and/or ASIC architecture and micro-architecture</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>2+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Experience working with DV teams or integrating models into verification flows</li><li>Experience with SystemC or TLM-based modeling</li><li>Experience correlating functional models against RTL simulation or emulation</li><li>Experience developing or calibrating performance models</li><li>Familiarity with Modern C++ (20 and beyond)</li><li>Experience with PyTest, GoogleTest, or similar test frameworks</li><li>Experience with multi-threaded simulation</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Cupertino - 165,200.00 - 223,600.00 USD annually 
USA, TX, Austin - 143,700.00 - 194,400.00 USD annually</div>

Pre-Silicon SoC Modeling Engineer, Annapurna Labs Machine Learning Accelerators, AWS

All Points Logistics

<div><div>Data Engineer
 <div></div><div><div>Huntsville , Alabama
</div>Direct Hire
Apr 9, 2026
</div></div><div>*US CITIZENSHIP REQUIRED* 
*ACTIVE DoD SECRET CLEARANCE REQUIRED* 
*THIS IS A SIX MONTH POSITION WITH POTENTIAL TO EXTEND* 
 
DESCRIPTION OF POSITION/DUTIES: 
 
All Points is seeking a Data Scientist / Data Engineer &ndash; Supply Chain Analytics to support the Army Materiel Command at Redstone Arsenal in Huntsville, AL. This is a six 
month, full time position with potential to extend and requires 100% on site support. There is no remote work option. THIS IS A SIX MONTH POSITION WITH POTENTIAL TO EXTEND. 
 
The selected candidate will support Army Supply Chain Command Orchestration and Monitoring operations as a hybrid data scientist and data engineer. This role operates at the intersection of data engineering and applied machine learning, owning both the data pipelines that move supply chain data and the models and analytics that extract operational insight. 
Working under the technical direction of a Senior AI Solutions Engineer, the candidate will build, optimize, and maintain production grade analytics that enable supply chain mapping, disruption detection, and risk visibility across priority weapons systems and materiel programs. This is a mission driven, production cadence role, not a research only position. 
 
Duties may include but are not limited to:
<ul><li>Build and maintain supply chain mapping constructs that trace multi-tier supplier relationships, component dependencies, foreign ownership indicators, and program linkages</li>
<li>Design, optimize, and maintain data pipelines ingesting supply chain data from government and commercial sources into Snowflake and downstream analytics environments</li>
<li>Develop and enhance disruption alerting models to detect supply chain stress signals, including single-source dependencies, supplier financial distress, geopolitical exposure, and lead-time anomalies</li>
<li>Apply machine learning and AI techniques to supply chain datasets, including entity resolution, anomaly detection, risk scoring, and predictive modeling</li>
<li>Write, optimize, and maintain complex SQL queries and Python-based transformation logic against Snowflake data warehouses</li>
<li>Produce analytic outputs that support Red Team vulnerability assessments, Blue Team mitigation planning, and executive decision-support dashboards</li>
<li>Participate in data quality validation, confidence scoring, and model monitoring workflows</li>
<li>Maintain pipeline documentation, data dictionaries, model artifacts, and data provenance per program governance standards</li>
<li>Support government-directed onboarding of new data sources, including schema mapping and integration into existing pipelines</li>
</ul>EDUCATION:
<ul><li>Bachelor&rsquo;s degree from an accredited college in a related discipline</li>
</ul>YEARS OF EXPERIENCE:
<ul><li>Eight (8) to ten (10) years of relevant experience preferred 
Minimum of four (4) years of combined data science and data engineering experience required</li>
</ul>SKILLS/CERTIFICATIONS:
<ul><li>Demonstrated supply chain domain knowledge, including supplier networks, procurement data, logistics, or defense materiel programs</li>
<li>Proficiency in Python for data engineering, analytics, and machine learning workflows</li>
<li>Strong SQL skills, including complex queries, window functions, and performance optimization</li>
<li>Hands-on Snowflake experience in a production analytics environment</li>
<li>Experience building and maintaining ETL/ELT pipelines using orchestration frameworks (Airflow, dbt, Spark, or equivalent)</li>
<li>Experience applying ML or AI techniques to real-world structured datasets in production or near-production environments</li>
<li>Strong documentation practices supporting data lineage, auditability, and governance</li>
<li>Experience with defense supply chain datasets (CAGE codes, NSNs, DLA/GIDEP) preferred</li>
<li>Experience with entity resolution, graph-based supply chain mapping, or network analysis preferred</li>
<li>Familiarity with AWS or other cloud data platforms in GovCloud or regulated environments preferred</li>
<li>Familiarity with CUI handling and NIST 800-171 data governance requirements preferred</li>
</ul>SECURITY CLEARANCE:
<ul><li>US Citizenship required</li>
<li>Active DoD Secret security clearance required</li>
</ul>Positions with All Points are Full-Time, Direct, and include a comprehensive benefits package. For more information, please visit our Career Portal: 
https://www.allpointsllc.com/careers/ 
 
ALL POINTS IS AN EQUAL OPPORTUNITY EMPLOYER</div></div>

2033 Cleared Data Scientist/Data Engineer – Supply Chain Analytics (Secret Clearance Required)

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