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.

• Design, build, and deploy ML models using production test data to predict optical module performance and identify potential failures before they occur • Apply rigorous statistical methods to validate model performance • Extract complex datasets from production databases using SQL queries and manage the transformation of that data into a format ready for ML model training • Perform data hygiene, normalization, and feature engineering on manufacturing data to ensure high-quality inputs for ML training • Implement LLM-based solutions to analyze and summarize complex manufacturing line performance statistics • Develop automated tools that assist project planning personnel to make key supply chain decisions • Work closely with hardware, product, and project engineering teams to understand the optical module production process and ensure solutions meet defined technical requirements and deliver tangible business impact • Stay current with AI/ML developments and integrate relevant advancements into ongoing projects and technical plans

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.

Overview Mercury Ignite. Kick-start your career with Mercury Ignite: Graduate Program in Data Science and Machine Learning is a 12-month structured journey that offers hands-on experience across real business projects and rotations within the Enterprise Data Science organization at Mercury Insurance. We are one team. The Enterprise Data Science team (EDS) is a technology team focused on accelerating Mercury’s data-driven transformation to support growth, operational excellence, and AI-enabled business processes. Geo-Salary Information Job Summary  We are seeking curious, passionate, and hard-working graduates from data science, computer science, data analytics, business analytics, statistics, mathematics, physics and machine learning or any other analytical / quantitative academic fields to participate in our remote graduate program. In this program, you will have two, six-month rotations focused on the below two functions: Data Science – Focuses on analytics, experimentation and AI to uncover insights, improve business decisions and drive business growth. Machine Learning – Focuses on designing, training, evaluating, and deploying machine learning models and supporting pipelines to solve real business problems at scale. This includes feature engineering, model experimentation, performance evaluation, and working with production systems to responsibly operationalize models. Responsibilities Job Function - Analyze insurance and customer data to identify trends, optimize growth strategies and support business decision making - Develop, implement and evaluate predictive models using machine learning to improve risk assessment, pricing and claims outcomes - Partner with cross functional teams to translate business problems into data driven solutions and measurable outcomes - Design and execute experiments to measure the impact of new initiatives and growth strategies - Ensure data quality, integrity and compliance with governance standards to maintain trusted, actionable datasets - Leverage AI and machine learning techniques to enhance predictive insights, automate processes, and responsibly scale data driven decision making Qualifications Education Requirements  - Be legally eligible to work in the U.S. - Recently completed a bachelor's or both bachelor's and master's degree in data science, computer science, data analytics, business analytics, statistics, mathematics, physics and machine learning or any other analytical / quantitative academic fields - Able to provide a cumulative GPA, as reported by your school. Minimum 3.5 GPA required. - Graduation date on or after November 2025 but no later than June 2026 - Planning to seek full-time employment by June 2026 Preferred Skills & Abilities  - Excellent verbal and written communication - Good problem-solving skills - Willingness to independently learn and make an impact within a team environment - Strong programming skills in at least one of the following: Python, SQL, R, C++, Rust, Go, or C#. - Good understanding of different data structures and algorithms - Strong programming skills in Python, with experience using it for data analysis, modeling, or building reproducible data pipelines and analytical workflows - Experience with SQL and relational data concepts - Familiarity with Git-based version control - Experience with data and ML python libraries such as scikit-learn, pandas, XGBoost, NumPy, and NLP Libraries - Background in another programming language (e.g., R, C++, Rust, Go) is welcome, provided there is interest in working primarily in Python and SQL Physical Requirements Physical Actions  Required job duties are essentially sedentary in nature, consisting of occasional walking, standing, lifting, and/or carrying ten pounds maximum. About the Company Why choose a career at Mercury? 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: https://www.mercuryinsurance.com/about/careers Perks and Benefits Why a Mercury Ignite Graduate Program - Entry-level role with real-world experience in areas of AI, Data and Automation - Fulltime opportunity to gain hands-on experience with programs and projects - Assigned buddy to support with team assimilation - Earn a competitive salary with benefits If you’re interested in launching your career with Mercury Insurance - Apply today! Mercury is an equal opportunity employer, committed to the strength of a diverse workforce. Pay Range USD $80,000.00 - USD $100,000.00 /Yr.