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2mo ago

Data Analyst

FocusKPI Inc. New York, NY

New York, NY

2mo ago Closed

$40+/hr Contract Analyst Analytics Business Intelligence

This position is no longer accepting applications (closed Sep 2, 2026).

Job Description

Contract Data Analyst role onsite in New York for five months focused on pricing operations, reporting, and analytics, with a pay rate of $40 per hour.

Responsibilities

Manage seller performance by creating and maintaining management dashboards and reports.
Generate targeted insights to inform the development of new seller offers.
Spearhead the deployment of pricing strategies within the client's pricing engine.
Test and review pricing configurations to confirm accuracy and proper functionality.
Identify, investigate, and resolve discrepancies uncovered during pricing system implementation.
Audit pricing data to verify accuracy and adherence to established guidelines.
Communicate effectively with team members and stakeholders about changes, updates, and issue resolutions in the pricing system.
Engage in day-to-day problem analysis, code execution, data analysis, and root-cause tracing to promptly address issues, including missed credits outside the crediting logic.

Requirements

3+ years of experience in operations, ideally in pricing operations, system implementation, or related roles in financial services.
Bachelor's degree in Business, Economics, Accounting/Finance, Computer Science, Math, Physics, Engineering, or other quantitative field.
SQL and Excel proficiency is mandatory.
Experience in coding and/or data visualization (for example Tableau).
Python experience is a plus.
Familiarity with business intelligence visualization tools.
CPA or CFA preferred.
Strong analytical and problem-solving skills with meticulous attention to detail.
Excellent communication and collaboration abilities for cross-functional teamwork.

Technologies

SQL
Excel
Tableau
Python

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2mo ago

Data Analyst II

Fabletics El Segundo, CA

El Segundo, CA

2mo ago Closed

$100k - $115k/yr Full time Analyst Analytics Business Intelligence

This position is no longer accepting applications (closed Sep 2, 2026).

Job Description

Fabletics is seeking a Data Analyst II to join its Data Analytics Team in El Segundo, CA on a hybrid schedule. The role emphasizes SQL data extraction, Tableau-based reporting, and close collaboration with Merch & Planning to translate data into actionable business strategies. The position offers a salary between USD 100,000 and 115,000 per year.

Responsibilities

Prepare data and analyses for Fabletics' business teams, with emphasis on Merch & Planning; deliver actionable insights and help translate findings into implementable strategies.
Develop intermediate to advanced SQL queries to pull data from Snowflake with accuracy and efficiency.
Oversee Tableau as the BI platform, including data modeling, establishing internal style standards, building and maintaining automated reports, and training end users on data analysis best practices.
Think creatively about various Merch & Planning analytics use cases and identify the data needed to realize them.
Collaborate with data engineering to propose improvements to the data architecture.
Drive innovation to move stakeholders toward more automated and scalable processes.

Requirements

Strong personal integrity, solid work ethic, and a desire to grow in the role.
Minimum 1-3 years of experience in a quantitative analytics role, with advanced SQL skills to extract data and build reports; solid understanding of relational databases and BI tools; aptitude for learning complex data concepts.
Experience creating data visualizations in Tableau, Looker, or similar visualization platforms.
Proficiency with Microsoft Excel, including pivot tables, formulas, and charting.
Ability to translate data analysis into actionable business recommendations.
Proven ability to manage multiple tasks and balance competing project priorities.
Excellent written and verbal communication skills for effective stakeholder engagement.
Interest in applying strategic thinking and analytical skills in a fast-paced, high-growth environment.
Collaborative mindset and willingness to partner with teammates and stakeholders.

Technologies

SQL
Snowflake
Tableau
Looker
MS Excel
Heap
Segment Customer Data Platform

Benefits

Hybrid Work Schedule*
Discretionary Paid Time Off*
Summer Fridays*
Healthcare Plans
Employee Discounts
401k
Annual Bonus Program
Equity Program*
And More

Why Work in Data Analytics at Fabletics?

Be part of the broader Data Analytics organization within TechStyle Fashion Group, a team of 60+ members, collaborating with analysts, scientists, and engineers at various levels.
Work with a leading data technology stack including Snowflake, Tableau, Heap, Segment CDP, modeled reporting data warehouses, and more.
Enjoy clear career advancement opportunities in a fast-growing company, with personalized tracks across Data Analytics, Data Engineering, Data Science, Business Strategy, Product Management, Software Engineering, and more.

Where we are

This role is based at Fabletics' El Segundo headquarters, with a hybrid work arrangement.

Security Alert: Protect Yourself from Scams

Fabletics is committed to legitimate recruitment practices. Initial outreach typically comes from official email addresses and LinkedIn; beware of deviations. Personal data and sensitive information will not be solicited during the application process. Interviews are conducted by phone, in person, or through approved platforms such as Teams or Zoom, and never via messaging apps or other calling methods.

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2mo ago

Data Analyst

Avantor Rensselaer, NY

Rensselaer, NY

2mo ago Closed

$63k - $101k/yr Full time Analyst Analytics Business Analytics

This position is no longer accepting applications (closed Sep 2, 2026).

Job Description

A Data Analyst role within Avantor's Advanced Laboratory Services in Rensselaer, NY, offers a hybrid work arrangement and centers on analyzing inventory and operational data, building dashboards, and delivering data-driven insights to enhance procurement and supply chain performance.

Responsibilities

Examine and interpret complex data sets related to inventory, procurement, and operations to inform decisions and boost performance.
Create and maintain Power BI dashboards, automated reports, data models, and KPI tracking tools.
Monitor inventory health, supplier performance, service levels, stock availability, and operational metrics, while identifying trends, risks, and opportunities for improvement.
Refine inventory strategies through demand planning, PAR level analysis, replenishment modeling, and reduction of excess or obsolete inventory.
Uphold data integrity through governance, auditing, validation, and exception-based reporting processes.
Assess workload and capacity to optimize staffing, resource planning, and organizational growth.
Lead process-improvement efforts by automating reporting, enhancing data quality, and deploying scalable operational solutions.
Collaborate cross-functionally with operations, procurement, quality, finance, IT, and customer stakeholders to translate business needs into actionable insights and decision-support tools.
Present findings, recommendations, and business cases to leadership while supporting audits, compliance requirements, and continuous improvement initiatives.

Requirements

Three or more years of experience in data analytics, business intelligence, inventory management, supply chain, procurement, or related operational environments.
Proven ability to analyze inventory, purchasing, order management, and operational performance data to drive business decisions.
Advanced proficiency in Microsoft Excel, including PivotTables, Power Query, complex formulas, and large dataset analysis.
Experience developing Power BI dashboards, data models, KPI reporting, and automated operational reports.
Working knowledge of SQL; experience with Snowflake, SAP, ERP, inventory management, or similar business systems is preferred.
Skilled in integrating and validating data from multiple sources while ensuring data accuracy and integrity.
Experience creating KPIs, forecasting models, exception reporting, and actionable business recommendations.
Strong understanding of data governance, master data management, reporting controls, and data quality standards.
Excellent analytical, problem-solving, communication, and stakeholder management skills.
Ability to present complex data insights to both technical and non-technical audiences.
Demonstrated ability to prioritize multiple projects, meet deadlines, and work independently in a regulated, customer-focused environment.
Detail-oriented with a strong commitment to accuracy, compliance, and continuous improvement.
Experience supporting audits, process improvement initiatives, and operational reporting is preferred.
Self-driven, adaptable, and proactive in identifying opportunities to improve processes and business outcomes.
Education: High school diploma or GED.

Technologies

Microsoft Excel
Power BI
Power Query
SQL
Snowflake
SAP
ERP

Benefits

Comprehensive medical, dental, and vision coverage
Wellness programs
Eligible for medical coverage starting Day 1
Paid Time Off (PTO)
Company-paid holidays
Choice holidays
Flexible Spending Account (FSA) and Health Savings Account (HSA)
Commuter benefits
401(k) retirement plan
Tuition assistance
Employee Stock Purchase Plan discount

Pay Transparency

The expected pre-tax pay for this position is $62,500.00 - $100,625.00
Actual pay may differ depending on relevant factors such as prior experience and geographic location.

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2mo ago

Machine Learning Engineer

Goliath Partners San Francisco, CA

San Francisco, CA

2mo ago Closed

$250k - $250k/yr Full time Ai Ml Artificial Intelligence Data Analysis

This position is no longer accepting applications (closed Sep 2, 2026).

Job Description

Goliath Partners is an early-stage AI fintech startup focused on real-time decisioning and data-driven risk analytics. This onsite Machine Learning Engineer role in San Francisco centers on designing and shipping production-ready ML models, building data pipelines and APIs, and steering end-to-end projects from research to deployment. The position offers a compensation of USD 250,000 per year.

Responsibilities

Design and scale ML models that address affordability, risk, and predictive analytics.
Build robust data pipelines and APIs to operationalize ML at scale.
Collaborate with product, data, and engineering teams to deliver customer-facing features.
Experiment with diverse approaches, identifying when ML is appropriate and when it is not.
Drive continuous improvement in model performance, monitoring, and reliability.

What you’ll do

Develop and scale ML models for affordability, risk, and predictive analytics.
Architect data pipelines and APIs to bring ML into production at scale.
Collaborate with product, data, and engineering teams to ship customer-facing features.
Experiment with different approaches, knowing when to use ML—and when not to.
Push forward innovation in model performance, monitoring, and reliability.

Who you are

Strong product mindset with a passion for solving real customer problems.
Hands-on ML engineer comfortable going end-to-end (research, data pipelines, production).
Experienced in Python, modern ML frameworks, and distributed systems.
High-quality standards but able to move fast and ship iteratively.
Excited about working in a high-ownership, early-stage startup environment.

Requirements

Strong product mindset with a passion for solving real customer problems.
Hands-on ML engineer comfortable going end-to-end (research, data pipelines, production).
Experienced in Python, modern ML frameworks, and distributed systems.
High-quality standards but able to move fast and ship iteratively.
Excited about working in a high-ownership, early-stage startup environment.

Technologies

Python

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2mo ago

Senior Machine Learning Engineer

Siemens Raleigh, NC

Raleigh, NC

2mo ago Closed

Full time Senior AI Ai Ml

This position is no longer accepting applications (closed Sep 2, 2026).

Job Description

Senior Machine Learning Engineer at Siemens in Raleigh, NC (onsite), leading LLM powered application development on AWS and owning the end-to-end model lifecycle with MLOps.

Responsibilities

Develop LLM driven applications by architecting retrieval augmented generation pipelines, coordinating prompts, building tools and agents, implementing safety controls, and creating evaluation harnesses; measure latency, cost, and quality.
Oversee the full ML lifecycle from data curation and feature engineering to training or fine tuning (LoRA or QLoRA), A/B testing, deployment, monitoring, and ongoing enhancement of models and prompts.
Deploy scalable AWS services using EKS, ECS and Lambda; leverage SageMaker, Bedrock, EMR, MSK, and Step Functions; implement observability with CloudWatch and OpenTelemetry and apply cost-control practices.
Establish MLOps and governance practices including CI/CD for models, model/version registries, data and prompt lineage, evaluation gates, and responsible AI controls.
Collaborate with Brightly across asset-management use cases to design ML and LLM solutions, working with product managers and UX to ship customer‑facing features that improve reliability, safety, and sustainability.
Conduct exploratory data analysis across structured, semi-structured, and unstructured data to reveal patterns, correlations, feature importance, and data quality issues.
Perform in-depth research on asset-related, operational, and domain datasets to uncover root causes, trends, and predictive signals.
Maintain a pragmatic, product‑oriented approach with a bias toward measurable outcomes and rapid iteration with stakeholders.
Practice engineering excellence by delivering production‑quality Python, designing reliable APIs and services, and upholding testing and observability standards.
Provide collaborative leadership by mentoring peers and influencing architectural decisions across teams.

Requirements

8 to 10 years of overall software or ML engineering experience, including at least 2 years building and operating production ML systems.
More than 1 year of hands-on LLM application development (RAG, fine‑tuning, prompt engineering, evaluators/guardrails, agentic workflows) using Langchain and Langgraph.
3+ years of AWS proficiency, with core services (EKS/ECS, Lambda, S3, DynamoDB or RDS, Step Functions, IAM) and ML stack familiarity (SageMaker, Bedrock or HF on AWS).
Modeling and frameworks expertise with Python, PyTorch, and Hugging Face ecosystem; experience with vector stores (OpenSearch, PGVector, Pinecone), embeddings, retrieval, and NLP/LLM evaluation metrics.
MLOps experience including CI/CD for ML, model registries, experiment tracking, telemetry/monitoring, and automated retraining; Docker/Kubernetes and CI pipelines (GitHub Actions or GitLab CI).
Data engineering fluency covering ETL/ELT, streaming and batch processing (Spark/Flink), and data quality and governance controls for ML.

Technologies

Python
PyTorch
Hugging Face ecosystem
Langchain
Langgraph
SageMaker
Bedrock
OpenSearch
PGVector
Pinecone
Spark
Flink
AWS
EKS
ECS
Lambda
S3
DynamoDB
RDS
Step Functions
IAM
EMR
MSK
CloudWatch
OpenTelemetry
Docker
Kubernetes
GitHub Actions
GitLab CI
MLflow
Kedro
SageMaker Pipelines

Nice to Have

Experience with distributed training (FSDP, DeepSpeed), RLHF, or optimization on Inferentia/Trainium.
Exposure to sustainability, asset management, or intelligent operations domains.
Security and compliance knowledge for enterprise ML systems.

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2mo ago

Machine Learning Engineer - Computer Vision & Data Systems

Apple Seattle, WA

Seattle, WA

2mo ago Closed

$175k - $309k/yr Full time Artificial Intelligence Big Data Bigdata

This position is no longer accepting applications (closed Sep 2, 2026).

Job Description

Apple’s Seattle site is looking for a Machine Learning Engineer who specializes in computer vision and large-scale data systems. You will design production-grade algorithms and build scalable data pipelines that enable real-time sensing and data intelligence across core product experiences. This onsite role in Seattle, WA offers a competitive salary and opportunities to advance research into practical, high-impact systems.

Responsibilities

Architect and maintain expansive data processing pipelines that support diverse data sources and modalities, prioritizing efficiency, scalability, and reliability.
Develop and optimize computer vision models that power key product experiences, including image understanding, multi-view geometry, 3D reconstruction, and visual recognition.
Collaborate with engineering, research, and data teams to translate product requirements into technical solutions, prototype models, run large-scale experiments, improve data quality, and ensure smooth production integration of algorithms.
Explore emerging areas such as large language model powered agents, retrieval-augmented systems, and tool-oriented reasoning to enhance internal workflows and data operations.

Requirements

PhD in a relevant field with research directly related to computer vision, large-scale data systems, or multimodal learning.
Experience designing or evaluating agentic systems, including LLM-powered tools, RAG pipelines, or automated data reasoning workflows.
Familiarity with prompt engineering, tool-use patterns, and LLM model behavior.
Experience deploying ML models at scale, including monitoring, evaluation, and continuous improvement.
Knowledge of data quality assessment, dataset curation methodologies, and evaluation frameworks.
Experience with GPU-based optimization, large-batch training, or distributed training.
Strong cross-functional collaboration skills and the ability to lead technical initiatives.
Robust foundation in computer vision, with experience in deep learning-based vision models and at least one area such as detection, segmentation, 3D vision, geometric methods, tracking, or self-supervised learning.
Hands-on experience building ML models using PyTorch or TensorFlow.
Experience designing or optimizing large-scale data pipelines (distributed ETL, dataset generation, annotation workflows, data validation, or high-throughput processing).
Proficiency in Python or C++ for algorithm development and data processing.
Experience working with distributed computing frameworks (e.g., Spark, Ray, or equivalent).

Technologies

PyTorch
TensorFlow
Python
C++
Spark
Ray

Benefits

Base pay range for this role is USD 175,000 to 308,500 per year.
Apple employees have opportunities to become shareholders through discretionary employee stock programs, including restricted stock units and the Employee Stock Purchase Plan with discounted stock purchases.
Comprehensive medical and dental coverage, retirement benefits, access to discounted products and free services, and reimbursement for certain educational expenses including tuition.
The role may be eligible for discretionary bonuses or relocation support.
Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and terms of the applicable plan or program.

Pay & Benefits details

Base pay is determined within a range based on skills, qualifications, experience, and location.
In addition to base pay, employees have the opportunity to participate in Apple stock programs and receive discretionary restricted stock unit awards.
Eligible employees may participate in the Employee Stock Purchase Plan to purchase Apple stock at a discount, and benefits include comprehensive medical and dental coverage, retirement benefits, discounts on products, free services, and reimbursement for certain educational expenses, including tuition.
The role may be eligible for discretionary bonuses or commission payments as well as relocation, subject to eligibility and plan terms.
Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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2mo ago

Machine Learning Engineer

Hang Los Angeles, CA

Los Angeles, CA

2mo ago Closed

Full time Engineer Learning Machine

This position is no longer accepting applications (closed Sep 2, 2026).

Job Description

Hang is seeking a Machine Learning Engineer to design, build, and deploy models that enhance our loyalty platform and drive data driven decisions.

Responsibilities

Design, build, and deploy machine learning models to improve customer personalization, predictive analytics, and automated decision making on Hang's platform.
Analyze large datasets to identify trends and inform model development and business strategies.
Continuously test and refine algorithms to boost accuracy and efficiency.
Collaborate with software engineers, data scientists, and product managers to integrate ML models into the platform and ensure seamless deployment.
Stay up to date with the latest developments in machine learning and AI, and explore new techniques and technologies that could benefit Hang.
Provide insights and guidance on best practices in machine learning and contribute to the technology strategy.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field; PhD is a plus.
5+ years of experience in machine learning and data related roles.
Proven experience as a Machine Learning Engineer or in a similar role.
Strong programming skills in Python and familiarity with ML frameworks such as TensorFlow or PyTorch.
Experience with data processing and data analytics.
Experience with vector databases and managing high dimensional data; familiarity with Redis, Milvus, Pinecone, Weaviate, Chroma, or Faiss is required.
Knowledge of machine learning techniques and algorithms, including fine tuning processes and methodology.
Experience deploying Large Language Models (LLMs) in production environments, including optimization and scaling considerations.
Experience with Snowflake, Postgres, RDS, Redis and AWS.
Excellent problem solving skills and ability to work in a fast paced environment.
Strong communication skills and ability to work well in a team.
Experience with Ruby is a plus.

Technologies

Python
TensorFlow
PyTorch
Redis
Milvus
Pinecone
Weaviate
Chroma
Faiss
Snowflake
Postgres
RDS
AWS
Ruby

Benefits

Top-tier health, vision, and dental insurance, including plans with $0 employee cost.
Unlimited PTO / sick leave
Competitive salary & equity compensation.
Quarterly company offsites