Role Description We are seeking a highly skilled Senior Data Scientist to join a fast-paced SaaS organization on a contract basis. This role is ideal for a hands-on data science professional with deep expertise in machine learning, Snowflake Cortex ML, Python, advanced SQL, and MLOps automation. The successful candidate will partner closely with business stakeholders to develop, optimize, and deploy production-grade machine learning solutions that drive business value. This is a 3 to 6-month contract with potential for permanent conversion, targeting a start date of August 1. Key Responsibilities - Machine Learning & Data Science - Design, develop, and enhance production-grade machine learning and predictive analytics models to solve complex SaaS business problems. - Maintain, optimize, and evaluate existing ML models to ensure continuous improvements in accuracy, performance, and scalability. - Apply statistical modeling and advanced machine learning techniques to extract actionable business insights from enterprise data. - Snowflake Cortex ML Development - Develop, deploy, and scale machine learning solutions natively using Snowflake Cortex ML and its broader AI capabilities. - Optimize model execution, feature engineering, and data processing architectures directly within the Snowflake ecosystem. - Collaborate with data engineering and platform teams to seamlessly integrate Cortex ML and Snowpark workflows into production systems. - MLOps & Pipeline Automation - Build, automate, and maintain robust end-to-end machine learning pipelines for model training, validation, and deployment. - Implement and govern MLOps workflows to support automated model monitoring, versioning, retraining, and continuous integration/continuous delivery (CI/CD). - Improve the reliability, automation, and scalability of production machine learning environments using Jupyter Notebooks and orchestration tools. - Data Integration & Stakeholder Collaboration - Perform complex SQL-based data extraction, transformation, feature engineering, and integration of third-party data sources. - Partner directly with cross-functional stakeholders in Product, Engineering, and Business teams to translate operational requirements into technical AI solutions. - Document workflows and present clear technical findings, methodologies, and strategic recommendations to both technical and non-technical audiences. Qualifications - 7 or more years of professional experience in Data Science or Machine Learning. - Demonstrated experience developing, optimizing, and supporting production-grade machine learning and predictive models. - Strong industry experience within a Software-as-a-Service (SaaS) or modern digital product environment. - Hands-on experience building and deploying machine learning solutions utilizing Snowflake Cortex ML. - Expert-level programming skills in Python and advanced SQL querying. - Proven experience establishing and automating MLOps pipelines, including model deployment, monitoring, versioning, and CI/CD. - Strong background in data integration, data quality verification, and advanced feature engineering. - Experience collaborating directly with business stakeholders to translate business needs into technical AI and ML solutions. Preferred Qualifications - Hands-on experience with Large Language Models (LLMs) or Generative AI integrations. - Experience utilizing Snowpark and modern Snowflake AI/ML platform capabilities. - Practical familiarity with Git, version control systems, and enterprise data pipelines. - Experience using cloud-based AI platforms and advanced production analytics tools. Core Skills & Attributes - Exceptional analytical, problem-solving, and statistical modeling capabilities. - Strong communication and presentation skills, with the ability to translate technical AI concepts into clear business value. - Excellent stakeholder management and collaboration skills across cross-functional engineering, product, and business domains. - Self-motivated with a strong attention to detail and the ability to operate independently in a fully remote environment. Benefits - Competitive salary - Remote location - Senior Level (7 or more years of experience)

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Role Description As Lumen continues this journey, Corporate Finance is playing a critical role in shaping the future through data and AI. We are seeking a Senior Data Scientist who is excited by the opportunity to turn information into impact. In this role, you’ll leverage Databricks, Generative AI, and advanced analytics to create scalable solutions that empower smarter decision-making. You’ll help expand self-service insights, automate finance processes, and uncover opportunities hidden within complex datasets. More than building models, you’ll help write the next chapter of Lumen’s transformation—where data becomes a strategic advantage and innovation drives meaningful business outcomes. This is a work from home position from within the US. Main Responsibilities - Build and enhance Databricks-based AI and analytics solutions that improve how Finance teams access and use insights. - Develop scalable data pipelines, workflows, and reporting solutions using Databricks, Data Factory, SQL, Python, and Power BI. - Apply statistical, forecasting, and machine learning techniques to solve business problems and strengthen decision support. - Automate manual processes, improve data quality, and strengthen the performance and reliability of analytics applications. - Partner across Finance, FP&A, Data Science, and IT to turn business needs into practical solutions and actionable insights. - Contribute to high-impact initiatives that advance how data and AI are used across Finance. Qualifications - 3–5 years of experience in data science, data engineering, analytics, or a related role - Strong Python and SQL skills - Experience with Databricks, PySpark, or Spark-based processing - Experience building data pipelines and working with large, complex datasets - Strong analytical, problem-solving, and communication skills Preferred Qualifications - Experience with forecasting, predictive modeling, statistical analysis, or machine learning techniques - Experience with Generative AI or LLM-based applications - Experience with Power BI or similar visualization tools - Exposure to financial data, FP&A, or enterprise reporting Compensation This information reflects the anticipated base salary range for this position based on current national data. Minimums and maximums may vary based on location. Individual pay is based on skills, experience and other relevant factors. - $84,629 - $112,838 in these states: AL, AR, AZ, FL, GA, IA, ID, IN, KS, KY, LA, ME, MO, MS, MT, ND, NE, NM, OH, OK, PA, SC, SD, TN, UT, VT, WI, WV, WY - $88,860 - $118,480 in these states: CO, HI, MI, MN, NC, NH, NV, OR, RI - $93,092 - $124,122 in these states: AK, CA, CT, DC, DE, IL, MA, MD, NJ, NY, TX, VA, WA Benefits - Comprehensive package featuring a broad range of Health, Life, Voluntary Lifestyle benefits and other perks that enhance your physical, mental, emotional and financial wellbeing.

Role Description At QuintoAndar Group, we are committed to promoting gender diversity across our teams. We want to see more women in strategic positions within our technical teams, and we believe we can achieve this through intentional opportunities and actions. This is part of a larger plan to strengthen an equitable culture across multiple aspects. In our Data Science team, you'll have the chance to work as a part of our product squads delivering features that enrich our product and a first-class experience that we are known for. You'll work alongside brilliant minds, with different skills: Product Managers, Designers, UX Writers, Data Scientists, Machine Learning Engineers, Software Engineers, etc. Be prepared for the job of your life - hard challenges, high expectations, intelligent life at work, meaningful conversations, outstanding productivity. Some of the specific problems we work in the Data Science team include: - Search and recommendation systems - Customer experience enhancement using ML such as in automatic routing of tickets - Pricing, liquidity and credit models - Building a platform that enables us to develop and deploy all those solutions Note: This is a senior position. We expect you to have at least 3+ years of experience applying data science and creating machine learning models. If you have the skills, but are starting your journey in Data Science, please apply to the Data Scientist job instead. Qualifications - Expert knowledge of machine learning concepts: regression and classification, clustering, neural networks, feature selection, cross-validation, curse of dimensionality, bias-variance tradeoff, model explainability, etc. - Good understanding of the engineering challenges to deploy machine learning systems to production - Proficiency in Python - Some knowledge or experience with Deep Learning - Experience with technical advice for other data scientists (technical leadership) - Excellent written and verbal technical communication skills - Good English skills (verbal and written) is mandatory Requirements - People that are seeking to learn and deliver real impact through Data Science - Have a MSc. (or Undergrad + intense experience) in machine learning, data science, information retrieval, ranking systems, recommender systems, natural language processing or other relevant fields - Have experience with applied generative AI: AI agents, prompt engineering, LLMs finetuning (lora, qlora, peft), LLM routing, LLM monitoring, LLM guardrails - Have experience working at fast-growing startups Benefits - Competitive salary - Profit sharing - Meal allowance - Health insurance - Dental plan - Life insurance - Childcare subsidy and Atypical Parenthood subsidy - Wellhub - Home office allowance - Employee assistance program (mental health, social, legal, and financial support) - Extended parental leave - Day off on birthday, Mother’s Day, and Father’s Day - Benefits Club (discounts on everyday services) - Discounts at educational institutions - Reading kit for children – PlayKids