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• Analyze behavioral patterns across the customer lifecycle to identify trends, usage archetypes, and opportunities to improve adoption, engagement, and retention. • Design experiments and measurement approaches to evaluate the impact of product and marketing changes - and help teams make decisions based on evidence rather than intuition. • Build models and datasets that improve how teams segment customers, forecast outcomes, and identify trends. • Apply machine learning and AI techniques where they solve practical problems, for both internal decision-making and customer-facing scenarios. • Partner with Data Engineering to improve the quality, reliability, and accessibility of core data and metrics. • Communicate findings clearly and directly so teams can make informed decisions without needing a statistics background.
• Actionable Insight: Generate compelling and actionable insights from complex, multi-source marketing data sets that directly inform channel investment, campaign design, and pipeline strategy. • Stakeholder engagement: Establish strong collaborative relationships with marketing leaders and operators across demand gen, partner, field, product marketing, and brand, delivering high-impact analytics initiatives that translate loose, evolving requirements into clear deliverables. • Attribution & Measurement: Design, build, and maintain the attribution framework for UpGuard – spanning first and multi-touch attribution and incrementality testing – and clearly communicate the trade-offs and assumptions behind each lens. • Channel & Program Analytics: Develop a deep, first-principles understanding of channel logic across paid media, organic, content, lifecycle, partner, and field, and build the metrics, models, and dashboards that let each program owner self-serve their performance. • Data Products: Partner with the data engineering team to design, construct, and maintain foundational marketing data assets – translating loose marketing requirements into well-specified dbt models that the whole organisation can rely on. • Business Intelligence: Partner strategically with marketing stakeholders to provide robust self-service and conversational analytics capabilities, using design thinking principles to build user-friendly dashboards for funnel performance, channel ROI, partner sourced pipeline, and field event attribution. • Deep Dive analysis: Personally conduct thorough, hands-on, technical analysis to diagnose and solve the most significant marketing challenges – from channel saturation and diminishing returns to lead quality decay and campaign cannibalisation. • Commercial Analysis: Provide ongoing operational support to the commercial growth of the organisation, connecting marketing investment to pipeline, ARR, and payback in ways that finance and the executive team trust.
Premium boutique software development company that helps brands with big ideas to make a difference in people’s lives.
• Build and deploy advanced predictive models for lead scoring, agent matching, price and time-on-market estimation, and conversion likelihood. • Develop production-grade RAG and GraphRAG pipelines, construct complex knowledge graphs across listings, agents, and clients, and design retrieval and ranking systems for unstructured data. • Write robust data transforms in Databricks (using SQL and PySpark) and author highly performant SQL queries across ClickHouse and PostgreSQL. • Partner closely with engineering teams to ship model and LLM outputs to production environments, frequently utilizing Inngest. • Analyze MLS data to surface actionable market trends and directly feed data-driven product features. • Design and analyze product experiments utilizing PostHog, and build comprehensive dashboards and analyses within Hex and Metabase. • Act as a strategic partner by translating ambiguous business questions into clear, actionable, and data-backed recommendations.
Tiger Analytics is a fast-growing advanced analytics consulting firm, recognized as a trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data.
Role Description We are looking for a Senior Data Scientist with a good blend of data analytics background, practical experience in Operation research strategies and Pricing Analytics within supply chains, and strong coding capabilities to add to our team. - Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming. - Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG. - Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization. - Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain. - Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions. - Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies. - Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement. - Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization. - Collaborate, coach, and learn with a growing team of experienced Data Scientists. Qualifications - Proven experience 10+ years working as a Data Scientist, with a focus on supply chain optimization and inventory allocation. - MS or PhD in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related field. - Experience with using mathematical programming solvers such as Gurobi, Xpress MP, CPLEX, or Google OR Tools in applications. - Solid understanding of statistical methods, optimization techniques, and predictive modelling concepts. - Strong proficiency in programming languages such as Python, Pyspark and SQL, and experience working with data analysis and machine learning libraries. - Ability to apply various analytical models to business use cases. - Exceptional communication and collaboration skills to understand business partner needs and deliver solutions and explain to business stakeholders. Benefits This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility. Company Description Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce. - Market leaders in AI and analytics consulting in the CPG & retail industry. - Over 40% of our revenues coming from the CPG & retail sector. - Fastest-growing sector with an emphasis on beefing up talent.
Guidehouse, a "next-generation consultancy" and a portfolio company of Veritas Capital, provides management, risk consulting, and technology services to help cl
Role Description We are currently searching for a Computer Scientist to independently provide support services to satisfy the overall operational objectives of the National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health (NIH). This is a full-time, remote opportunity in Rockville, MD. - Perform software development to include the definition of subsystem interface specifications, software modeling, and implementing software design. - Design, build, and maintain a robust and flexible informatics infrastructure to support data collection from automated high-through-put screens. - Collaborate with teams of engineers and scientists in completing phases of projects by developing subsystems or components, which are part of those projects. - Work with biologists and chemists to analyze data from assays and screens. - Conduct theoretical and experimental studies of integrated computerized information systems. - Apply the techniques of parallel computing to computationally intensive tasks that are encountered in biomedical applications. - Implement algorithms for highly parallel computer structures containing many processor elements in application areas such as computational chemistry and structural biology. Qualifications - Master’s degree. - A minimum of FOUR (4) years of experience in computer science or related field. - Extensive experience with one or more programming languages. - Expertise in theoretical computing (such as algorithm and data structure development, computational complexity, information or database theory, etc.). - Must be able to obtain and maintain a Federal or DoD "public trust"; candidates must obtain approved adjudication of their public trust prior to onboarding with Guidehouse. Candidates with an active public trust or suitability are preferred. Requirements - Strong communications skills, both oral and written. - Able to successfully manage several high-priority tasks at the same time. Benefits - Medical, Rx, Dental & Vision Insurance - Personal and Family Sick Time & Company Paid Holidays - Parental Leave - 401(k) Retirement Plan - Group Term Life and Travel Assistance - Voluntary Life and AD&D Insurance - Health Savings Account, Health Care & Dependent Care Flexible Spending Accounts - Transit and Parking Commuter Benefits - Short-Term & Long-Term Disability - Tuition Reimbursement, Personal Development, Certifications & Learning Opportunities - Employee Referral Program - Corporate Sponsored Events & Community Outreach - Care.com annual membership - Employee Assistance Program - Supplemental Benefits via Corestream (Critical Care, Hospital Indemnity, Accident Insurance, Legal Assistance and ID theft protection, etc.) - Position may be eligible for a discretionary variable incentive bonus
Role Description 829 is seeking a highly analytical, technical, and hands-on leader to build, scale, and operationalize the next generation of data infrastructure, analytics systems, and process automation architecture across the agency. This role leads a small but specialized team, with support of contract engineers and analysts, to architect, implement, and maintain the underlying data systems that power measurement, forecasting, and operational efficiency. This role primarily manages and oversees Apollo, 829’s proprietary data centralization and insights platform that powers operational efficiency, campaign performance, and decision-making across 829’s client base. This is not a traditional agency reporting and BI role. This is a hands-on technical leadership position with responsibilities that span strategy, engineering, product management, and implementation. The right candidate will: - Write and review SQL & Python. - Influence data models and design ETL workflows. - Prototype features within Apollo. - Operate effectively in a lean environment without large in-house engineering teams. This is a player/coach role ideal for someone who loves combining strategy with execution. You will: - Architect measurement systems. - Implement forecasting and predictive models. - Shape the product roadmap for Apollo. - Set the analytics foundation for a 300-person agency navigating rapid change in marketing, media, and AI. You must be comfortable being scrappy, resourceful, and hands-on, while also operating as a cross-functional leader who can influence the broader organization. What You'll Do - Product Ownership & Technical Architecture: Apollo (60%) - Own the evolution of Apollo, 829’s data centralization and management platform. - Develop and manage the product roadmap — balancing technical feasibility, organizational needs, and high-impact use cases. - Own the Apollo budget and make resource-allocation decisions based on ROI and efficiency gains. - Lead technical direction and collaborate with engineers (contract) to deliver scalable improvements. - Identify and implement AI-driven workflows that materially reduce manual reporting, accelerate insight generation, and improve operational efficiency. - Act as the primary strategic resource for feature development, pressure testing all features and functions. - Ensure data models, pipelines, and system architecture support reliable analytics and performance reporting. - Build and standardize frameworks and documentation that ensure consistent adoption across teams. - Analytics, Measurement & Tracking Leadership (20%) - Guide the agency’s measurement philosophy and the systems that support it. - Oversee conversion tracking, ad-tracking, and analytics service delivery. - Build measurement frameworks, tagging schemas, ETL flows and data governance processes. - Implement forecasting and predictive modeling tools that support client performance. - Team Leadership (20%) - Lead a small but growing team that delivers exceptional agency and client outcomes. - Directly manage a team of full-time specialists and bench of contract labor. - Expand the team as needed to achieve performance objectives. - Support talent development through training and process development. - Spearhead change management and adoption of Apollo, measurement processes, and analytics tools across the agency. - Serve as a member of the leadership team, championing continuous improvement, data-driven decision making, and operational discipline. Qualifications - 10+ years’ experience in the agency space, with a preference for experience in analytics, product, and/or hybrid roles within digital marketing, media or agency environments. - Proven ability to run small teams and ship high-impact data/analytics solutions with constrained resources. - Hands-on experience with SQL, Python, DBT, APIs, ETL pipelines, and data warehousing (BigQuery, SnowFlake). - Experience operating without a large in-house engineering team and successfully shipping data products in lean environments. - Ability to read, review, and meaningfully contribute to application-layer code (Node, React, or similar) is strongly preferred. - Strong understanding of tracking architecture (GA4, GTM, server-side, conversion APIs). - Demonstrated experience creating repeatable forecasting and analytical models to predict and optimize client campaign performance. - Strong analytical capabilities, with a history of implementing systems that enable better data collection, retention and analysis. - Strong interpersonal skills and demonstrated ability to communicate with a variety of stakeholders. Nice-To-Haves - Experience with React/Node and custom front-end applications. - Prior experience building internal analytics or performance insight platforms. - Experience implementing custom AI tools, including chat and agentic applications. - Background in managing contract and near/off-shore resources. Benefits - Remote Workplace: Option to work at the office in Boston or remotely in various states. - Paid Time Off: Generous paid vacation benefits that increase each year, 12 Company Holidays, and Summer Fridays. - 401K + Match: 401K plan with 4% Safe Harbor employer match after one year of employment. - Life Insurance Benefit: No-cost coverage to ensure peace of mind for your family. - Short Term Disability Benefit: Coverage for illness or injury that keeps you out of work. - Healthcare: Competitive healthcare plans with significant employer coverage. - Commuter Benefits: Pre-tax funds allocation towards your commute. - Continuing Education: Access to webinars, learning platforms, and funding for conferences.
Role Description We are looking for a Senior Data Scientist to join us as the first Data Scientist on a new product we are building. This is a founding role: you will shape the data science function from the ground up, set technical direction, and own the end-to-end delivery of intelligent systems that define how our product creates value. You will tackle open-ended problems involving: - Task Mining - Process Mining - Behavioral workflow analysis - Pattern discovery - Predictive modeling - Applied GenAI/ML systems The goal is not just to build models, but to turn raw interaction data into measurable product and business impact: discovered workflows, bottlenecks, optimization opportunities, and scalable foundations for future DS/ML work. This is a remote position. We do not offer visa sponsorship or assistance. Resumes and communication must be submitted in English. Qualifications - 5+ years of professional experience in Data Science, Machine Learning, or Applied ML roles. - Demonstrated experience operating as the sole or lead Data Scientist on a product or team — owning problems end-to-end without senior DS supervision. - Strong experience with supervised and unsupervised ML, modern ML/data tooling, and the judgment to select the right approach for the problem. - Practical familiarity with representation learning, sequence modeling, Transformers, LLMs, or GenAI systems where relevant to product use cases. - Experience handling large-scale structured, unstructured, event, or interaction datasets. - Advanced proficiency in Python and SQL, with hands-on experience using tools such as PyTorch, scikit-learn, pandas/Polars, experiment tracking, and production ML workflows. - Experience deploying ML models, data pipelines, or intelligent systems into production. - Familiarity with Task Mining, Process Mining, event-log analysis, behavioral analytics, workflow automation, or adjacent domains. - Advanced degree in Computer Science, Data Science, AI, Statistics, Mathematics, or a related field is a plus; equivalent practical experience is strongly valued. Requirements - A founder’s mindset: full responsibility for outcomes, not just deliverables. - Comfort operating in high ambiguity: able to turn unclear product goals, noisy data, and incomplete requirements into an executable roadmap. - Strong business sense — connects technical work to commercial impact and measurable product value. - Pragmatic technical judgment — knows when to use advanced ML, when to simplify, and when better data, labeling, or evaluation is the real bottleneck. - Ability to build foundations for rapid scaling: reusable datasets, pipelines, metrics, evaluation frameworks, and modeling patterns future DS/ML hires can build on. - Highly proactive problem solver who acts without waiting for detailed instructions. - Excellent communication skills, with the confidence to push back constructively and propose direction. Nice to Have - Previous experience as a first or early Data Scientist at a startup or new product line. - Direct experience with Task Mining, Process Mining, workflow intelligence, RPA, or productivity analytics. - Experience with LLMs and Generative AI applications, especially evaluation, structured outputs, semantic labeling, summarization, or human-in-the-loop workflows. - Experience working with privacy-sensitive behavioral, productivity, or user-interaction data. - Experience with product experimentation, causal inference, or measuring the impact of workflow/process interventions. - Knowledge of MLOps and distributed processing frameworks, such as Spark. - Experience with cloud environments, especially GCP.
At JETNET, you’ll be part of an innovative company that stands at the forefront of aviation data solutions with a sterling reputation in the industry. Ready to take flight with us? Apply today and become a part of the JETNET Team!
Role Description JETNET is seeking an Aviation Intelligence Data Scientist to help shape the future of aviation data intelligence. This is not a traditional analytics role. It is a strategic, hands-on opportunity for a data scientist who can architect intelligence frameworks, build AI-enabled workflows, and transform vast historical and live aviation data into scalable, production-ready capabilities. In this role, you will sit at the center of JETNET’s evolution into a modern Data Operations & Aviation Intelligence function. You will partner closely with leadership, engineering, and frontline research teams to develop intelligence models and systems that improve data quality, accelerate researcher workflows, strengthen product innovation, and expand JETNET’s competitive advantage in the aviation intelligence space. - Lead the design of JETNET’s post-ingestion intelligence layer, converting raw aviation data into structured, workflow-ready insights - Build and refine intelligence frameworks such as confidence scoring, inference models, entity resolution, ownership continuity, and relationship strength modeling - Develop AI-assisted workflows and LLM-enabled tools that surface ranked suggestions, next-best actions, and confidence-weighted recommendations for researchers - Identify and prioritize high-value data gaps and enrichment opportunities across aircraft, companies, contacts, and related aviation entities - Design graph-based models and linking strategies to strengthen relationship discovery and reduce duplication across datasets - Apply process mining and operational analytics to improve the ingest, verification, and publishing lifecycle, reducing bottlenecks and cycle time - Partner with aviation researchers to build practical, scalable solutions that improve consistency, speed, and data confidence in daily workflows - Lead end-to-end data science initiatives from problem framing through experimentation, validation, deployment, and performance monitoring - Collaborate closely with the CTO and Engineering Team to productionize models and intelligence capabilities within modern data environments - Translate complex findings into clear, executive-ready reporting, dashboards, and recommendations that support strategic decision-making Qualifications - Proven success independently leading end-to-end data science initiatives from concept to production deployment - Strong expertise in AI/ML, including building, evaluating, and optimizing production-grade models and LLM-assisted systems - Experience designing intelligent workflows that blend automation, analyst judgment, and measurable performance improvement - Hands-on experience with graph-based linking, probabilistic modeling, entity resolution, and relationship discovery techniques - Strong operational mindset, with experience using analytics to identify process optimization opportunities and improve workflow outcomes - Experience working with both structured and unstructured data, including OCR and extraction workflows - Advanced proficiency in Python and SQL, with experience in modern cloud data environments and model deployment practices - Strong business judgment and the ability to prioritize work that delivers meaningful product, operational, and customer impact - Excellent communication skills, including the ability to explain complex technical concepts to non-technical audiences and executives - Curiosity, ownership, and a builder mentality, with enthusiasm for solving difficult data problems in a specialized industry Requirements - Location: Open to applicants based in the USA with current legal authorization to work. - Compensation Range: $100,000 - $135,000/year Benefits - Remote Work Flexibility: Enjoy a balanced work-life arrangement with remote flexibility, empowering you to deliver your best work from home. - Comprehensive Paid Time Off: We understand the value of rest and recharge, so we offer competitive PTO to support a healthy work-life balance. - Comprehensive Benefits Coverage: With health, dental, and vision benefits, we prioritize your well-being so you can focus on making an impact.
• Responsible for all aspects of clinical trial data management from study start up through database lock and study close. • Ensures optimized data collection, flow and access across EDC and non-EDC data sources. • Ensures accuracy, consistency, completeness and CDISC compliance of all clinical databases. • Operate as a key member of the Clinical Operations team.
Role Description They are seeking a Data Scientist to join the team. Do you love working in machine learning pipelines with big data from day one? Do you have hands-on experience in state-of-the-art NLP (e.g., transformers, BERT, few-shot learning, fine-tuning) and information retrieval (e.g., vector-based semantic search, reranking, hybrid search)? Do you want to continue to work at the frontier of advanced ML and NLP, at a mission-driven startup where they love what they do? If this sounds like you, this might be a dream job! What You’ll Own - Recommender Systems: Ensuring the product makes high-quality recommendations to both job seekers (as a “GPS” for their careers) and employers (as a “talent radar”). - Taxonomies: Using data and AI to model and make sense of the evolving landscape of skills, occupations, and careers in a changing labor market. - Agentic AI Solutions: Prototyping and evaluating new AI-powered functions for job seekers, employers, and case workers. - Data Science Strategy: Serving as an advisor and expert on strategy and roadmap decisions, evaluating major developments in the field, and ensuring the use of state-of-the-art techniques. - Mentorship/Leadership: Acting as a dedicated mentor and tech lead, assisting with the quality, rigor, and acceleration of projects and tasks. Qualifications - 5+ years of combined experience in industry and/or graduate-level research. - Proficiency training and evaluating ML and NLP models using both structured and unstructured data with reproducible results. - Expert-level programming and software engineering skills and a track record of delivering re-usable and well-documented code. - Practical knowledge of using LLMs to accelerate model development, for example through synthesizing training data or automating evaluation. - Proven ability to own a problem space from 0 to 1, translating vague business problems into production models. - Comfortable navigating ambiguity and working with competing priorities. - Strong communication skills to present models and actionable insights to stakeholders with varying levels of technical expertise. Bonus Points - Specific examples of recommendation systems, taxonomies, or AI agents that you have built. - Experience with data engineering, analytics, dashboards, or BI tools. - Experience with A/B testing or causal analysis. - An economics or social sciences background, especially any experience analyzing or modeling labor market data. - Recognized expertise through publications, conference talks, open-source software releases, or other public artifacts related to state-of-the-art tools, models, and techniques. Our Tech Stack - Languages: SQL, Python - Data orchestration: Airflow - Data storage and warehousing: S3, Glue, Redshift, PostgreSQL, MongoDB - Machine learning and experimentation: AWS SageMaker - Visualization and reporting: Looker, QuickSight - Infrastructure: AWS ecosystem Your Education Your alma mater isn’t their focus. Your grit, hunger, and drive are. If you learn continuously, tackle challenges head-on, and know your strengths and gaps intimately—you’re their person. Location United States or Canada (Remote, ET Preferred) Travel Expectations You may be expected to travel up to once per quarter. Compensation The base salary range for this role is $115,000-$140,000. This range reflects the varying levels of expertise and responsibilities that will be determined through the interview process, based on applied experience and other criteria established by the hiring committee. Hiring Journey The hiring process is designed to help you assess whether this role and the culture are the right fit based on your unique skills, mindset, and experiences. They move fast and work with intensity, so they want you to get a real sense of that from the start. - Online Application - Initial Screen with Director of People & Culture - Interview with Hiring Manager - Performance Challenge - Panel Interview - Final Decision Generally, this entire process takes around 4 weeks, although the timing can vary due to specific candidate circumstances. Company Snapshot - Team: 30-50 across US and Canada (hubs in NYC and Toronto) - Customers: Workforce development agencies and intermediaries, government agencies, employers - Industry: SaaS/AI technology - Funding: Bootstrapped 0-1, then raised funding led by JP Morgan - Structure: Growth, Customer Success, Product, Engineering, Data, People & Culture, Finance & Operations Our Core Principles - Be Curious - Drive to Outcomes - Raise the Bar - Speed Matters - Own It - We Over Me Use of AI in Hiring They use artificial intelligence (AI) tools to make the hiring process more efficient, consistent, and equitable—never to replace human judgment. AI is used in the following ways: - Screening support: AI may help compare applications against the skills and experience required for a specific role. These skills are defined by the hiring team for each position. A human reviews each application, with the AI assessment as just one input. - Interview support: In some interviews, they may use an AI notetaker to summarize the discussion so interviewers can focus on being present in the conversation. - Insights, not decisions: AI provides data points to support the team’s evaluation but does not make or recommend final hiring decisions. Every hiring decision is made by people. They will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Please contact them to request an accommodation. They are proud to be an equal opportunity workplace. They celebrate diversity and are committed to creating an inclusive environment for all employees. They do not discriminate on the basis of race, religion, color, gender identity, sexual orientation, age, disability, veteran status, or other applicable legally protected characteristics. They encourage people of different backgrounds, experiences, abilities, and perspectives to apply.
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Python, SQL, AI, AI/ML, BigQuery, Cloud
