This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As part of this transformation, we’re building a best-in-class performance marketing engine—and we’re hiring a Sr. Data Scientist, Marketing to help us push it to the next level. - Develop and deploy advanced statistical and machine learning models to support key marketing initiatives—including media mix modeling, attribution, targeting, and customer LTV forecasting - Design and implement robust experimentation frameworks to power A/B and multivariate testing across marketing channels and customer journeys - Lead exploratory data analysis to uncover opportunities for growth, personalization, and efficiency—leveraging internal and third-party data sources - Build predictive models that inform campaign strategy, audience segmentation, and churn prevention - Collaborate with Data Engineering and Analytics teams to build scalable data pipelines and ensure data integrity for modeling and reporting - Partner with performance marketing, CRM, brand, and regional teams to translate analytical findings into business action - Develop clear, concise, and compelling data stories for leadership and cross-functional stakeholders - Stay ahead of the curve on new methodologies, tools, and privacy trends in marketing data science—and help drive their adoption across the organization. Qualifications - 5+ years of experience in data science with a Bachelor’s or Master’s degree or 2+ years with a PhD, preferably with a focus on marketing, customer analytics, or growth in a fintech or B2C tech environment - Strong programming skills in Python or R, especially for modeling, data manipulation, and visualization - Expertise in statistical methods (e.g., regression, clustering, time-series, causal inference, uplift modeling, Bayesian approaches) - Deep experience with A/B testing, experiment design, and measurement - Proficiency in SQL and working with large-scale datasets from data warehouses (e.g., Snowflake, Redshift, BigQuery) - Familiarity with data visualization tools (e.g., Looker, Tableau, Power BI) - Hands-on experience with marketing platforms (e.g., Google Ads, Meta, CRM tools) is a plus - Strong communication skills with the ability to distill complex analysis into clear insights and actionable recommendations - Comfort operating in a fast-moving, ambiguous, and highly collaborative environment - Multilingual skills or global market experience is a plus. Requirements - This position will be remotely based in the United States Benefits - Remote first flexibility - Generous PTO - 13 Paid Holidays - Medical / Dental / Vision Insurance - Life, Disability, and other benefits - 401k with competitive Employer Match - Community Service Days - Generous Parental Leave - Anticipated Base Pay: $145,000 - $200,000 + participation in our annual bonus plan

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Data Scientist/Senior Data Scientist, you will drive our predictive analytics innovation. Your primary goal will be to design, build, and deploy new predictive models across our entire product suite, including iWave, Ascend, and AdvancementRM. - Build Predictive Models: Design and implement machine learning models to predict donor behavior, giving capacity, and engagement propensity across all Kindsight products. - Maximize the Value From Client and Third-Party Data: Evaluate the wide-range of data gathered from clients and current third-party vendors to identify new metrics and insights using existing data. - Identify New Data Collection Opportunities: Identify additional data that could be collected within each product to develop stronger predictive models. - Benchmarking: Design new metrics to benchmark client fundraising potential and performance. - Partner with Head of AI: In close collaboration with our Head of AI, build agents and generative AI that leverages new predictive model results to fuel fundraising efforts. For Sr Level, in addition to the above: - Architect & Mentor: Lead the design of scalable ML pipelines and mentor junior data scientists on best practices in statistical modeling and experimental design. Qualifications - Intermediate Experience: At the junior level, 3+ years of data analytics, data science, and machine learning experience. - Senior Experience: 6+ years of data analytics, data science, machine learning experience, and preferably management experience. Experience working in Agile environments, with a strong understanding of Scrum principles. - Technical Acumen: Mastery of Python or R to clean, structure, and model data. Preferably, experience with AWS. - Problem Solving: Strong, detail-oriented problem solving skills and ability to work independently. - Excellent Communicator: Strong written and verbal communication skills with a focus on internal communication across teams. Bonus Points - Familiarity with Salesforce - Familiarity with CRMs, ERPs, or fundraising technology. Compensation Range $110k-$175k CAD base annually, plus bonus, based on experience, market benchmarks, and role complexity. We aim to offer fair, competitive pay that reflects your skills and the market. Equal Opportunity Statement This advertised position is for an existing vacancy at Kindsight. At Kindsight, we’re proud to be a place where everyone belongs and has an equal opportunity to contribute, thrive and grow. We hire based on skills, potential, and impact, and we believe our differences fuel innovation. We welcome all individuals and do not discriminate on the basis of gender identity and expression, race, ethnicity, disability, sexual orientation, colour, religion, creed, gender, national origin, age, marital status, pregnancy, sex, citizenship, education, languages spoken or veteran status. We’re building a workplace where everyone has the opportunity to do meaningful work and make a difference. AI Tools in Recruitment We leverage artificial intelligence (AI) tools to support certain aspects of our recruitment process. These tools may help with resume screening, drafting job descriptions, creating interview questions and occasionally identifying potential candidates. All hiring decisions are made by our people, not AI. Our intent is to use AI thoughtfully to streamline administrative tasks, improve the candidate experience and support fair, unbiased hiring practices consistent with industry standards.

• Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing → prototyping → evaluation → production → monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. • Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. • Optimize the scalability, performance, and reliability of AI Team solutions by implementing best practices and leveraging industry-standard technologies. • Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. • Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. • Evaluate and optimize model prototypes for real-world performance and integrate ML models into production systems with partner teams to communicate and understand technical requirements and challenges.

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. We are seeking a Senior / Lead Data Scientist with strong expertise in forecasting, tree-based models, and large-scale data processing. The role requires hands-on experience with PySpark, Databricks, and Azure and the ability to lead end-to-end model development and deployment. Experience with MLOps / DevOps is a strong plus. Key Responsibilities - Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools. - Apply advanced data science techniques to identify patterns, inefficiencies, and bottlenecks across logistics and operations. - Build scalable data pipelines and analytical models using PySpark for large-scale datasets. - Develop predictive and prescriptive models to support decision-making in areas such as demand forecasting, routing, and inventory management. - Collaborate with cross-functional teams including operations, product, and engineering to translate business challenges into analytical solutions. - Communicate insights and recommendations clearly to stakeholders through data storytelling, visualizations, and presentations. - Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards. - Collaborate, coach, and learn with a growing team of experienced Data Scientists. - Stay connected with external sources of ideas through conferences and community engagements