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🔥 Data Analyst (Product Analytics Focus with Cross-Functional Collaboration)

Posted about 5 hours ago

📍 United States

🔍 Software Development

🏢 Company: Servant👥 11-50 Consulting Advice Professional Services

🔧 Requirements

Advanced SQL skills for querying complex datasets, optimizing performance, and building custom data models.
Proficiency in Python for data manipulation, statistical analysis, automation, and developing quick ETL workflows.
Experience with product analytics tools such as Google Analytics, Amplitude, Mixpanel, or similar platforms.
Familiarity with UI/UX analytics, including heatmaps, clickstream analysis, and user flow tracking.
Expertise in creating dashboards and reports using Tableau, Power BI, or other visualization tools.
Strong foundation in statistical analysis, A/B testing, and experimentation methodologies.
Experience with cohort analysis, retention analysis, and growth metrics to support business growth initiatives.
Proven ability to work effectively with diverse stakeholders across Product, Marketing, Finance, Operations, and Donor Development.

💡 Responsibilities

Analyze user behavior, feature adoption, retention trends, and app engagement to identify opportunities for product improvement.
Conduct cohort analyses, funnel tracking, and A/B test evaluations to measure the impact of product changes and experiments.
Partner with Product Managers to translate business questions into analytical solutions, providing data-driven recommendations to influence product strategy.
Collaborate with teams across Marketing, Finance, Operations, Donor Development, and other departments to understand their data needs and deliver actionable insights.
Support marketing initiatives with campaign performance analysis, segmentation strategies, and conversion tracking.
Provide financial analysis support related to donation trends, revenue forecasts, and operational efficiency metrics.
Contribute to donor analytics by tracking engagement, retention, and giving patterns to optimize fundraising strategies.
Write complex SQL queries to extract, manipulate, and analyze large datasets from Snowflake, BigQuery, and other data sources.
Use Python for data wrangling, statistical analysis, automation of repetitive tasks, and developing quick ETL pipelines as needed.
Independently identify and implement solutions to data challenges, minimizing dependencies on Data Engineers.
Design and build interactive dashboards in Tableau, Power BI, or custom solutions to visualize key KPIs such as MAUs, donation trends, campaign performance, and operational metrics.
Automate reporting processes to improve efficiency, reduce manual errors, and ensure consistent access to up-to-date data.
Continuously improve dashboards based on user feedback and evolving business needs, ensuring insights are both accessible and impactful.
Leverage product analytics tools (e.g., Google Analytics, Amplitude, Mixpanel) to analyze user interactions and behaviors within digital products.
Conduct heatmap analyses, clickstream tracking, and user journey mapping to identify friction points and areas for optimization.
Provide data-driven recommendations to Product and Design teams to enhance user experiences and improve conversion rates.
Design, implement, and analyze A/B tests to evaluate new product features, marketing campaigns, and operational changes.
Develop statistical models to forecast user growth, donor retention, and revenue trends based on historical data and predictive analytics.
Recommend growth strategies backed by data-driven experimentation and robust analysis.
Ensure data accuracy, consistency, and reliability across all reports and analyses by implementing data validation checks and monitoring data pipelines.
Partner with the Data Architect and Data Governance Lead to uphold data standards and best practices across the organization.
Proactively identify and resolve data discrepancies, ensuring high data integrity in all outputs.
Stay current on emerging trends in product analytics, data science, and business intelligence tools.
Experiment with new technologies, programming languages, and analytical methods to continuously enhance data capabilities.
Share knowledge and best practices with the broader ACoE team, contributing to a culture of continuous improvement and data literacy across the organization.

Python SQL Business Intelligence Data Analysis ETL Numpy Snowflake Google Analytics Amplitude Analytics Tableau Product Analytics REST API Pandas Communication Skills Analytical Skills CI/CD Problem Solving Written communication Reporting JSON Cross-functional collaboration Data visualization Financial analysis Data modeling A/B testing

Posted about 5 hours ago

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🔥 Senior Software Engineer, AI

Posted about 5 hours ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Fieldguide👥 101-250💰 $30,000,000 Series B 12 months agoArtificial Intelligence (AI)Document Management

🔧 Requirements

5+ years of engineering experience
Excitement for product-focused application of ML/AI - this will be a production-focused role
Exceptional technical proficiency with at least one programming language, particularly Python or TypeScript
Understanding of ML concepts like supervised/unsupervised/self-supervised learning, neural networks and deep learning
Understanding of modern ML/AI technologies, including natural language processing (NLP) and LLMs (e.g., GPT-3+, open source models, etc.), RAG architectures, and their applications
Experience architecting systems and data pipelines that can handle the ingestion, digitalization, storage, and retrieval of document-heavy data sets, including document processing, search, and classification
Experience in developing, testing, evaluating and deploying ML models
Ability to collaborate on all aspects of product strategy and UX
Experience shaping an early stage tech stack and product, and engineering organization

💡 Responsibilities

Be an essential technical contributor at a Series B company as it scales.
Play a leadership role on the end-to-end development of features, specifically in regards to making architectural decisions and trading off different approaches.
Bring a mindset of continuous improvement to your work. You’ll be responsible for making our technology and processes better over time.
Understand how to optimize for iteration speed while maintaining a high quality bar and technical rigor.

AWS Backend Development GraphQL PostgreSQL Python SQL Artificial Intelligence Cloud Computing Data Analysis Data Mining Full Stack Development Git Keras Machine Learning Numpy PyTorch React.js Software Architecture TypeScript Data engineering REST API Pandas React Tensorflow CI/CD DevOps NodeJS Software Engineering

Posted about 5 hours ago

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🔥 Senior Machine Learning Engineer

Posted about 5 hours ago

📍 USA

🧭 Full-Time

🔍 Audit and advisory

🏢 Company: Fieldguide👥 101-250💰 $30,000,000 Series B 12 months agoArtificial Intelligence (AI)Document Management

🔧 Requirements

4-5 years of experience in applied machine learning or related field
Strong proficiency in Python and its ML/data science libraries
Extensive experience with NLP techniques and generative AI technologies
Experience with LLMs and both text-to-text and text-to-image generative models
Proficiency in working with large datasets and creating ETL processes
Experience with version control systems (e.g., Git) and CI/CD practices
Ability to work in a fast-paced, changing startup environment

💡 Responsibilities

Collaborate with stakeholders to identify and map business problems to ML solutions
Design, develop, and implement ML models with a focus on NLP and generative AI applications
Curate, clean, and prepare data for model development and training
Create and maintain ETL jobs for data processing
Conduct rapid prototyping of ML solutions to quickly iterate on ideas
Stay current with the latest advancements in ML, particularly in NLP and generative AI
Collaborate with the platform engineering team to integrate ML solutions into the overall product architecture
Implement data flywheels to continuously improve ML features through increased usage
Define and implement ML performance metrics
Contribute to the product roadmap with ML-driven feature ideas
Be an essential technical contributor at a Series B-stage company as it scales

AWS Python SQL ETL Git Machine Learning Numpy Data science Pandas Tensorflow CI/CD A/B testing

Posted about 5 hours ago

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🔥 Data Scientist (NLP, Transformers, PyTorch, Deep Learning)

Posted about 8 hours ago

📍 Poland, Romania, Bulgaria, Estonia, Hungary, Ukraine

🏢 Company: SupportYourApp👥 1001-5000💰 over 2 years agoData Collection and Labeling UX Design Outsourcing Web Development Technical Support Call Center Information Technology Travel Software Social Media

🔧 Requirements

2.5+ years of commercial experience in Machine Learning (including NLP)
Fluency in written and spoken English or Ukrainian (C1-C2)
Experience working with transforming models (usage, re-training, fine tuning)
Experience with Deep Learning frameworks: Pytorch, Tensorflow
Solid experience with Python, OOP, Rest API (Flask, Celery)
Good knowledge of NLP tools and libraries: NLTK, Spacy, scikit-learn, GenSim
Experience with Seq2Seq models
Experience with Docker and Docker-compose for effective containerization and deployment strategies
Deep understanding of theoretical concepts Language modeling, Named Entity Recognition, text classification, clustering, topic modeling, embedding, ML metrics

💡 Responsibilities

Improve and maintain current solutions for support automation
Develop new features after being fully familiar with the architecture
Discuss the project strategy, brainstorm with the team

Docker Python Machine Learning MLFlow NLTK PyTorch Algorithms Data Structures REST API Pandas Tensorflow

Posted about 8 hours ago

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🔥 Junior Full Stack AI Engineer

Posted about 9 hours ago

📍 Worldwide

🧭 Full-Time

🔍 AI

🏢 Company: Creai

🔧 Requirements

Proficiency in Python and Java or Scala; familiarity with machine learning frameworks like TensorFlow or PyTorch and data libraries like pandas and scikit-learn.
Hands-on experience with AWS, Google Cloud, or Azure and their machine learning toolsets.
Proven ability to tackle complex problems using data analytics and predictive modeling.
Strong verbal and written communication skills with a team-oriented mindset, capable of working effectively with cross-functional teams.
Keen scientific curiosity with a commitment to staying updated on industry trends and best practices.
Familiarity with data structures, data modeling, and software architecture principles.

💡 Responsibilities

Design, build, and maintain efficient machine learning models and full-stack solutions from prototype to production, optimizing performance, scalability, and cost.
Work closely with data scientists, software engineers, and product managers to integrate AI models into broader software systems, ensuring seamless functionality.
Analyze large datasets, develop predictive models, and apply advanced statistical techniques to address client-specific challenges.
Continuously improve existing systems and algorithms for speed, efficiency, and reliability.
Utilize cloud platforms (AWS, Google Cloud, Azure) to deploy and scale AI solutions, leveraging services that enhance performance and cost-effectiveness.
Stay informed about the latest AI and machine learning trends and technologies, ensuring that Creai remains competitive.
Document development processes and present technical results to technical and non-technical stakeholders.

AWS Python SQL Cloud Computing Data Analysis Full Stack Development Java Machine Learning PyTorch Software Architecture Azure Pandas Tensorflow Communication Skills RESTful APIs Scala Data modeling

Posted about 9 hours ago

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🔥 Engineering Manager, Machine Learning

Posted about 12 hours ago

📍 United States

🧭 Full-Time

💸 185000.0 - 220000.0 USD per year

🔍 Software Development

🏢 Company: WellSaid

🔧 Requirements

5+ years of experience managing a software engineering team and a proven track record.
2+ years of experience using Cloud platforms (GCP, AWS, etc),
Background in Machine learning frameworks (such as PyTorch), and data processing tools (Spark, Pandas, etc.) are a big bonus but not mandatory.
You are proficient in software development practices, including specing, documenting, testing, reviewing, deploying, and monitoring, and are passionate about writing clean, defensible code.
Excellent communication and collaboration skills to work effectively with cross-functional teams, including software engineers, data engineers, product managers, execs, and other stakeholders.
You are flexible and capable of working with a diverse team with various communication styles and needs. You are empathic and supportive.
You create equitable processes across the entire employee lifecycle. You are particularly mindful of addressing the needs of marginalized people.
Experience in text-to-speech, speech-to-text, audio libraries, or cloud storage is a bonus.

💡 Responsibilities

Build and lead a high-performing and collaborative machine learning team, fostering an environment of innovation, growth, and accountability.
Collaborate with Product Management and other stakeholders to define, prioritize, and deliver the ML roadmap, aligning it with business goals and technical feasibility.
Ensure that complex projects are effectively scoped, planned, executed, and delivered on time while meeting cross-team quality standards.
Oversee multiple concurrent machine learning projects simultaneously, facilitating planning, and generally ensuring that deliverables are met on time.
Own and run team standups, sprint planning, and other delivery ceremonies.
Work one-on-one with team members to meet their needs, providing regular and constructive feedback. You’ll show concern and success for the well-being of others and do what you can to support people.
Conduct design, code and pull request reviews with the team.
Champion best practices in machine learning and software engineering including testing, documentation, readability, defensibility, etc.
Manage team resources effectively by prioritizing projects based on impact while balancing budget constraints for infrastructure (e.g., compute resources) or tooling needs.
Foster customer empathy within the team by introducing real-world use cases, facilitating discussions on customer pain points, reviewing feedback loops, and ensuring alignment with user needs.
All together you’ll foster an inclusive team culture and working environment.

AWS Leadership Project Management Python Software Development SQL Agile Cloud Computing Data Analysis GCP Git Machine Learning People Management Product Management PyTorch SCRUM Software Architecture Algorithms Data engineering Data Structures Pandas Spark Communication Skills CI/CD RESTful APIs Mentoring Team management Data modeling Debugging

Posted about 12 hours ago

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🔥 Senior Application Support Engineer

Posted about 13 hours ago

📍 India

🔍 Market Research and Analytics

🔧 Requirements

5+ years of proven experience in web application development or application support, particularly in systems with high uptime requirements.
Strong ability to troubleshoot issues with web/http traffic, python applications, and JS applications.
Proficient in Python, Docker, AWS, REST APIs, and database technologies.

💡 Responsibilities

Diagnose and resolve technical issues in data applications and platform services, including web application performance, optimizing SQL, Pandas, and PySpark queries, and interacting with REST APIs.
Work cross-functionally with data analyst teams and platform engineers to coordinate releases, onboard users, and maintain the uptime of critical Plotly Dash applications.
Identify and implement process improvements to streamline support workflows, reduce repetitive tasks, and improve application and data platform efficiency.
Promote and enforce application best practices, data software management, and cloud infrastructure to enhance system reliability and reduce technical debt.

AWS Docker Python SQL Git API testing REST API Pandas Spark CI/CD RESTful APIs Linux Troubleshooting Data modeling Scripting Data analytics Debugging

Posted about 13 hours ago

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🔥 Data Engineer

Posted about 14 hours ago

📍 United States

🧭 Full-Time

🔍 Sustainable Agriculture

🏢 Company: Agrovision

🔧 Requirements

Experience with RDBMS (e.g., Teradata, MS SQL Server, Oracle) in production environments is preferred
Hands-on experience in data engineering and databases/data warehouses
Familiarity with Big Data platforms (e.g., Hadoop, Spark, Hive, HBase, Map/Reduce)
Expert level understanding of Python (e.g., Pandas)
Proficient in shell scripting (e.g., Bash) and Python data application development (or similar)
Excellent collaboration and communication skills with teams
Strong analytical and problem-solving skills, essential for tackling complex challenges
Experience working with BI teams and tooling (e.g. PowerBI), supporting analytics work and interfacing with Data Scientists

💡 Responsibilities

Collaborate with data scientists to ensure high-quality, accessible data for analytical and predictive modeling
Design and implement data pipelines (ETL’s) tailored to meet business needs and digital/analytics solutions
Enhance data integrity, security, quality, and automation, addressing system gaps proactively
Support pipeline maintenance, troubleshoot issues, and optimize performance
Lead and contribute to defining detailed scalable data models for our global operations
Ensure data security standards are met and upheld by contributors, partners and regional teams through programmatic solutions and tooling

Python SQL Apache Hadoop Bash ETL Data engineering Data science RDBMS Pandas Spark Communication Skills Analytical Skills Collaboration Problem Solving Data modeling

Posted about 14 hours ago

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🔥 Staff Machine Learning Engineer

Posted 1 day ago

🧭 Full-Time

💸 185000.0 - 315000.0 USD per year

🔍 Financial Operations

🏢 Company: Ramp👥 501-1000💰 $150,000,000 Series D 11 months agoFinancial Services Finance FinTech

🔧 Requirements

Bachelor’s degree or above in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields with a minimum of 5 years of industry experience as a Machine Learning Engineer, Applied Scientist or Data Scientist
Strong python experience (numpy, pandas, sklearn, pytorch etc.) across ML techniques and back end engineering
Prior experience deploying Machine Learning models to production and making meaningful contribution to backend systems
Strong knowledge of SQL (preferably Snowflake, BigQuery)
Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions

💡 Responsibilities

Employ statistical and machine learning on large datasets to discover patterns of account takeovers and identity theft
Prototype and productionalize machine learning models and rules-based systems to protect user accounts
Partner closely with Identity Engineering and Data Platform teams to augment and leverage data across first and third party sources, ensuring we’ve added as much context as possible to every decision we make
Contribute to the culture of Ramp’s machine learning team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way

Backend Development Python SQL Machine Learning Numpy PyTorch Snowflake Data engineering Pandas Data modeling Software Engineering

Posted 1 day ago

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🔥 Backend Data Developer - Scraping & Conversión de Java a Python

Posted 1 day ago

📍 Argentina, Colombia, Peru, Bolivia, Plurinational State of, Mexico

🧭 Contract

💸 2300.0 - 2500.0 USD per month

🔍 Software Development

🏢 Company: Workana

🔧 Requirements

Experience with Selenium, Puppeteer or Playwright.
Experience with Java (Spring Boot, Jsoup, HttpClient) and Python (Scrapy, Selenium, Playwright, FastAPI).
Experience with pandas and NumPy.
Knowledge in SQL databases (PostgreSQL, MySQL, SQL Server).
Implementation of scrapers in scalable environments with Docker and Kubernetes.
Deployment in AWS or GCP.

💡 Responsibilities

Development and maintenance of scrapers for extracting data from web portals.
Refactorization and optimization of legacy scrapers in Java towards Python.
Implementation of more efficient architectures to improve performance.

AWS Backend Development Docker GraphQL PostgreSQL Python SQL Apache Airflow ETL GCP Java Java EE Kubernetes MySQL Numpy Spring Boot Data engineering FastAPI REST API Pandas Selenium CI/CD Microservices JSON Data management

Posted 1 day ago

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