Role Description - Strong Python and Jupyter notebook experience with heavy use of Pandas for joining, reshaping, aggregating, and validating multiple data frames. Experience with NumPy and SciPy statistics is highly preferred. - Hands-on experience building Monte Carlo simulations including distribution selection and fitting, sampling design, and interpreting P10 P50 P90 results. Experience handling correlated variables is a plus. - Experience converting complex Excel models into code by tracing formulas, documenting assumptions, and validating numeric accuracy. - Ability to build reliable data pipelines in Python including API authentication, pagination, schema normalization, error handling, and incremental refresh. - Strong SQL skills for extracting inputs from data warehouses or billing databases. - Experience with versioning and auditability beyond Git, including structured snapshot storage of inputs and outputs. - Comfort explaining model outputs and variance drivers to non-technical stakeholders and producing business-ready commentary. Qualifications - Prior work in FP&A, cloud economics, FinOps, or cost and usage modeling for AWS, Azure, or GCP. Company Description

Role Description En tant qu’Alternant(e) Data & Tracking, tu feras partie intégrante de l’équipe Performance et tu accompagneras un Lead Tracking expérimenté qui te formera pas à pas à l’implémentation de plans de taggage, au server-side tracking et à la collecte de données propres pour les clients. - Implémenter et maintenir des plans de taggage : - Configurer Google Tag Manager (Web et Server-Side) pour les clients. - Mettre en place le suivi GA4, les conversions Google Ads, Meta CAPI et les Enhanced Conversions. - Apprendre à structurer un dataLayer propre sur Shopify et d’autres CMS. - Travailler sur l’infrastructure server-side : - Participer aux déploiements sur Addingwell et Stape. - Configurer les sous-domaines, le DNS et le Consent Mode v2. - Comprendre pourquoi le server-side est le standard et comment le mettre en place de A à Z. - Assurer la qualité de la donnée : - Vérifier que les événements remontent correctement dans GA4 et les plateformes Ads. - Debugger les tags. - Auditer les setups existants. - Rédiger des recommandations pour les clients. - Participer aux campagnes d’acquisition (secondaire) : - Assister ponctuellement l’équipe sur la gestion de campagnes Google Ads et Meta Ads. - Comprendre comment la donnée que tu collectes alimente directement la performance publicitaire. Company Description

Role Description As our eCommerce Marketing Data Analyst, you aren’t just a "report puller." You are the navigator. You’ll be the person who connects the dots between a spike in Shopify traffic, a dip in Amazon conversion, and the inventory risk sitting in our warehouse. You’ll build the "single source of truth" that allows our leadership team to stop manual data mining and start making faster, smarter moves. - Owning the Dashboard: You’ll spend time in the trenches of Amazon Seller Central, Shopify Analytics, and GA4. You’ll clean the "messy" data and publish the weekly KPI reports that our team relies on. - Spotting the "Why": When sales spike or a conversion rate drops, you’ll be the first to flag it. You’ll surface the anomalies and trends so the GM and Brand Managers can act before a molehill becomes a mountain. - Financial & Inventory Integrity: You’ll help us bridge the gap between sales and the P&L. You’ll track our performance against financial targets and use statistical forecasting to make sure we have enough inventory to meet demand—without overstocking. - Collaborative Strategy: You’ll join our KPI review meetings not just to present charts, but to provide the context. You'll partner with Marketing and Ops to ensure our attribution models (especially for off-Amazon spend) actually make sense. Qualifications - You speak "eComm": You already know your way around AOV, CAC, ROAS, and LTV. You’ve handled customer cohort analysis and understand the nuances of Amazon’s reporting quirks. - You’re a Google Sheets/Excel Wizard: You don’t just do VLOOKUPs; you build clean, repeatable models that don’t break when someone else touches them. - You enjoy the "Puzzle": You actually like the challenge of unifying data from different platforms. You’re comfortable with tools like Looker Studio or Power BI to make data visual and easy to digest. - You’re a Clear Communicator: You can take a complex data trend and explain it simply to a non-technical stakeholder so they know exactly what the "takeaway" is. Benefits - Work from Anywhere: 100% Remote work environment. - Comprehensive Coverage: Paid Time Off (PTO), and Paid Holidays. - Competitive Pay: Hourly rate starts at $8 (still negotiable). - Rewards for Excellence: Incentives for Attendance, Referrals, and Work Anniversaries. Your Application Roadmap - Step 1 Resume Screening: Our hiring team reviews your experience to see how your unique skills align with our high-growth roles. - Step 2 Recruiter Interview: A human-to-human chat to discuss your career goals, experience, and what makes you tick. - Step 3 Online Assessment: This is your chance to shine! You’ll complete a role-specific test, a personality assessment, and your official GA Profile Form so we can advocate for you. - Step 4 Match Interview: You’ll meet with one of our US-based Senior Lead Recruiters for a deep-dive validation to ensure we’re matching you with the right opportunity. - Step 5 15-min Prep Call: We’ve got your back. Before the final round, your Recruiter will hop on a quick call to coach you, share insider tips, and ensure you’re 100% ready. - Step 6 Client Interview: The final step! You’ll meet the client to discuss how you’ll help them scale and succeed.

Role Description The Utah Jazz are looking for a Data Scientist to perform modeling and analysis that will help inform basketball decision-making. We are located in Salt Lake City, but are open to remote candidates (must be legally authorized to work in the United States). Duties & Responsibilities - Develop and maintain models to better predict basketball outcomes and facilitate better decision-making across Basketball Operations. - Perform ad hoc data analysis as necessary to help basketball decision-makers. - Interface with all departments within Basketball Operations (scouting, coaching, analytics, sports science) and strive to understand and meet their needs. - Identify, research, and implement opportunities for new models, data sources, and basketball analytics techniques. - Help maintain and test datasets used to perform analysis. - Maintain best practices for software development including test writing, documentation, and adherence to and improvement of coding standards. - Protect the reputation of the company. - Exemplify the Utah Jazz mission and values: transparent, all in, community obsessed, one team, and scrappy. - Accept other duties, as assigned. Competencies - Communicates Effectively – Develops and delivers multi-mode communications that convey a clear understanding of the unique needs of different audiences. - Demonstrates Self-awareness – Uses a combination of feedback and reflection to gain productive insight into personal strengths and weaknesses. Qualifications - Bachelor’s in Statistics, Data Science, Math or equivalent experience. - 2+ years of experience analyzing data and training statistical models in a production environment using Python or R. - 2+ years of experience with basketball data and the latest basketball analytics techniques. - 2+ years of experience with data visualization. - Expertise in statistics fundamentals and state-of-the-art predictive modeling techniques. - A desire to work in a startup-like environment where you will be empowered to make design decisions. - A track record of writing clean and well-documented code. - Enthusiasm for basketball. - Nice to have experience with MLOps. - Nice to have experience with SQL. - Nice to have experience with data engineering. - Must be legally authorized to work in the United States. Physical Demands - This person must be able to communicate and express themselves both written and verbally. - This person must be able to observe, inspect, estimate, and assess. - This person must be able to sit for long periods of time.