This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking curious, passionate, and hard-working students from quantitative academic fields to participate in our fully remote summer internship program. The program will be highly collaborative and immersive, with interns working on real business problems that can span multiple business units within the complex insurance landscape. As a Data Science Intern, you will support analytical projects on: - Identifying business opportunities - Answering business questions - Developing business solutions Interns will work with their managers and fellow interns within an interactive Agile framework that includes: - Daily stand-ups - Weekly tactical problem-solving sessions - Broader meetings within their respective functions Over the course of the summer, interns will ultimately build a minimum viable product (MVP) and have a “capstone” opportunity to present those findings to the Mercury leadership team. Internships will begin in June 2025. - 12-week remote summer internship - 40-hour work week - Paid Internship: $30/hour for undergraduates; $30/hour for graduate students - Future full-time opportunities may be available for high performers Qualifications - Be legally eligible to work in the U.S. - Pursuing a Bachelors (BS/BA) or Masters (MS/MA) degree in an information technology field - Able to provide current GPA, as reported by your school. Minimum 3.0 GPA required, 3.5 or higher GPA preferred. - Enrolled student attending a university program with an expected graduation date on or after August 2024 - Planning to seek full-time employment between December 2025 and September 2026 - Excellent verbal and written communication - Ability to manipulate and analyze data to address and solve business problems - Willingness to independently learn and make an impact within a team environment - Strong programming skills in Python or R, experience building dashboards - Preferred but not required: experience with SQL and Git/GitHub/GitLab Benefits - Obtain practical work experience in your field of interest - Network with other interns and industry professionals - Receive personalized coaching and mentorship - Work on real projects and initiatives - Earn a competitive salary Company Description At Mercury, we have been guided by our purpose to help people reduce risk and overcome unexpected events for more than 60 years. We are one team with a common goal to help others. Everyone needs insurance and we can’t imagine a world without it. Our team will encourage you to grow, make time to have fun, and work together to make great things happen. We embrace the strengths and values of each team member. We believe in having diverse perspectives where everyone is included, to serve customers from all walks of life. We care about our people, and we mean it. We reward our talented professionals with a competitive salary, bonus potential, and a variety of benefits to help our team members reach their health, retirement, and professional goals. Learn more about us here: Mercury Careers

The Position The Opportunity As a Data Scientist you will have a strong foundation in machine learning (ML), data science, and software engineering. You will have practical experience in building and deploying ML models and developing AI agents, particularly for tasks involving unstructured/structured data and workflow automation. As a Data Scientist you will have a strong foundation in machine learning (ML), data science, and software engineering. You will have practical experience in building and deploying ML models and developing AI agents, particularly for tasks involving unstructured/structured data and workflow automation. Key Responsibilities: - Machine Learning and Deep Learning: The candidate must be proficient in a wide range of ML algorithms, from traditional models like linear regression and decision trees to more advanced deep learning architectures such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). They should understand the principles behind model training, validation, and hyperparameter tuning. - Natural Language Processing (NLP): For extracting information from unstructured text, strong NLP skills are essential. Look for experience with techniques like tokenization, sentiment analysis, named entity recognition, topic modeling, and using pre-trained language models like BERT, GPT, or others from the Hugging Face ecosystem. - Data Handling and Feature Engineering: They should be adept at working with various data formats and have experience in data cleaning, preprocessing, and transforming raw data into useful features for ML models. This includes handling missing values, encoding categorical data, and scaling numerical features. - Programming and MLOps: Proficiency in Python is a must, along with a solid understanding of key libraries like Scikit-learn, Pandas, TensorFlow, and PyTorch. Experience with MLOps (Machine Learning Operations) practices, including model versioning, monitoring, and deployment on cloud platforms (AWS, Azure, or GCP), is crucial for building and maintaining robust solutions. - AI Agent Architectures: Look for a candidate who understands the components of an AI agent, including a Large Language Model (LLM) as the brain, tools for specific tasks, and a logical structure for decision-making. - Workflow Automation: The candidate should have practical experience in designing and implementing automated workflows. This involves integrating AI agents and ML models into existing business processes. They should be able to identify bottlenecks, map out a solution, and build the necessary connectors or APIs to execute tasks automatically. - Unstructured Data: The candidate needs to demonstrate expertise in handling various forms of unstructured data, including text, images, and audio. This involves building pipelines to ingest, process, and analyze this data to extract meaningful insights or trigger actions. Who you are - Problem-Solving: The ability to break down complex business problems into manageable, data-driven solutions is key. They should be able to think critically and creatively to solve real-world challenges. - Communication: A great candidate can clearly articulate technical concepts to non-technical stakeholders, explaining the "why" and "how" of their solutions. This is vital for collaborating with different teams and ensuring the project meets business goals. - Business Acumen: The best candidates understand the business context of their work. They should be able to connect their technical solutions directly to a positive impact on the company's bottom line or operational efficiency. Education & Academic Background - Minimum Requirement: A Bachelor’s degree in a highly quantitative field (Computer Science, Data Science or related field). - Preferred: A Master’s in a specialized domain such as Machine Learning, Computational Statistics, Operations Research, or a related quantitative discipline. - Proven Track Record: At least 7 years of professional experience in data science, with a clear history of taking AI applications from conceptualization to production environments. - Data Handling: Expertise in handling unstructured data - Advanced ML Expertise: Experience with supervised/unsupervised learning, deep learning (CNNs, Transformers), and reinforcement learning; proficiency in building agentic workflows, including RAG integration and LLM orchestration - Data Infrastructure: Expertise in SQL and experience working with cloud platforms (AWS, GCP, or Azure) - Large Language Model expertise required - Experience with Diagnostics and/or Pharmaceutical data is a plus Pleasanton location (where the team resides) is highly preferred. The position can be remote for exceptional candidates. Relocation benefits are not available for this posting The expected salary range for this position based on the primary location of California is $127,200 - $236,200.00. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below. Benefits #LI-PK1 Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

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. We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector, and we are beefing up our talent in the space. We are seeking an experienced Data Science Lead to lead our Pricing and Promotion Optimization team. In this role, you will drive the development and execution of product strategies that enhance pricing and promotion initiatives. The ideal candidate will have a strong background in product management with a focus on analytics-driven decision-making, as well as proven experience in roadmap planning and cross-functional team leadership. Key Responsibilities: - Work on the latest applications of data science to solve business problems in the optimization space for a CPG client - Effectively communicate the analytics approach and how it will meet and address objectives to business partners. - Product Roadmap Development: Create, manage, and communicate a clear roadmap and strategic vision for the pricing and promotion optimization product, aligned with business goals and market trends. Key activities include developing, maintaining, enhancing and scaling the product to various Markets. - Quarterly Planning: Design and implement quarterly plans, ensuring alignment with product goals, KPIs, and timelines. - Team Leadership: Lead and mentor a cross-functional team of 5-6 members, fostering a collaborative and high-performance environment. - Pricing & Promotion Strategy: Define and implement an optimization framework to optimize pricing and promotional Strategies. - Stakeholder Collaboration: Work closely with internal teams, including Marketing, Sales, Engineering, and Analytics, to gather requirements and translate them into actionable plans. - Market and Competitive Analysis: Conduct ongoing analysis of market trends and competitor strategies to identify opportunities and gaps. - Performance Monitoring: Track and analyze key metrics to ensure product success, and identify areas for improvement to drive product growth. - Collaborate, coach, and learn with a growing team of experienced Data Scientists. - Stay connected with external sources of ideas through conferences and community engagements. - Support demands from regulators, investor relations, etc., to develop innovative solutions to meet objectives utilizing cutting-edge techniques and tools.

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. We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector, and we are beefing up our talent in the space. We are seeking an experienced Data Science Lead to lead our Pricing and Promotion Optimization team. In this role, you will drive the development and execution of product strategies that enhance pricing and promotion initiatives. The ideal candidate will have a strong background in product management with a focus on analytics-driven decision-making, as well as proven experience in roadmap planning and cross-functional team leadership. Key Responsibilities: - Work on the latest applications of data science to solve business problems in the optimization space for a CPG client - Effectively communicate the analytics approach and how it will meet and address objectives to business partners. - Product Roadmap Development: Create, manage, and communicate a clear roadmap and strategic vision for the pricing and promotion optimization product, aligned with business goals and market trends. Key activities include developing, maintaining, enhancing and scaling the product to various Markets. - Quarterly Planning: Design and implement quarterly plans, ensuring alignment with product goals, KPIs, and timelines. - Team Leadership: Lead and mentor a cross-functional team of 5-6 members, fostering a collaborative and high-performance environment. - Pricing & Promotion Strategy: Define and implement an optimization framework to optimize pricing and promotional Strategies. - Stakeholder Collaboration: Work closely with internal teams, including Marketing, Sales, Engineering, and Analytics, to gather requirements and translate them into actionable plans. - Market and Competitive Analysis: Conduct ongoing analysis of market trends and competitor strategies to identify opportunities and gaps. - Performance Monitoring: Track and analyze key metrics to ensure product success, and identify areas for improvement to drive product growth. - Collaborate, coach, and learn with a growing team of experienced Data Scientists. - Stay connected with external sources of ideas through conferences and community engagements. - Support demands from regulators, investor relations, etc., to develop innovative solutions to meet objectives utilizing cutting-edge techniques and tools.