lead scientist

Huntington Bank

<div><h1 class="jobSectionHeader">Description</h1><div>
Summary:
</div><div><div><div><div>The Lead Data Scientist contributes to building and developing the organization&rsquo;s data infrastructure and supports the senior leadership with insights, management reports, and analysis for decision-making processes.
Duties and Responsibilities:
<ul><li>Performs advanced analytics methods to extract value from business data.</li><li>
Performs large-scale experimentation and build data-driven models to answer business questions.</li><li>
Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence.</li><li>
Determines requirements that will be used to train and evolve deep learning models and algorithms.</li><li>
Articulates a vision and roadmap for the exploitation of data as a valued corporate asset.</li><li>
Influences product teams through presentation of data-based recommendations.</li><li>
Evangelizes best practices to analytics and products teams.</li><li>
Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring.</li><li>
Performs other duties as assigned.</li></ul>
Basic Qualifications:
<ul><li>Master&rsquo;s degree in computer science, statistics, economics or related field</li><li>
5+ years of experience related work experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, scripting languages, and packages, including experience with big data analysis tools and techniques, and building and deploying predictive models, web scraping, and scalable data pipelines.</li></ul>
Preferred Qualifications:
</div></div></div></div><ul><li>PhD in computer science, statistics, economics or related fields</li><li>
Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling</li><li>
Strong experience with R, RSTudio, Python, SAS, SQL, NoSL</li><li>
Up-to-date knowledge of machine learning and data analytics tools and techniques</li><li>
Strong knowledge in predictive modeling methodology</li><li>
Experienced at leveraging both structured and unstructured data sources</li><li>
Willingness and ability to learn new technologies on the job</li><li>
Demonstrated ability to communicate complex results to technical and non-technical audiences</li><li>
Strategic, intellectually curious thinker with focus on outcomes</li><li>
Professional image with the ability to form relationships across functions</li><li>
Ability to train more junior analysts regarding day-to-day activities, as necessary</li><li>
Proven ability to lead cross-functional teams</li><li>
Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)</li><li>
Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)</li><li>
Demonstrated Expertise with at least one Data Science environment (R/RStudio, Python, SAS) and at least one database architecture (SQL, NoSQL)</li><li>
Financial Services background</li></ul><h3 class="jobSectionHeader">
#LI-NG1</h3><h3 class="jobSectionHeader">
#LI-Onsite 
</h3> 
Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay)
Yes
Workplace Type:
Office
Our Approach to Office Workplace Type
Certain positions outside our branch network may be eligible for a flexible work arrangement. We&rsquo;re combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.
Huntington is an Equal Opportunity Employer.
Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.
Note to Agency Recruiters: Huntington Bank will not pay a fee for any placement resulting from the receipt of an unsolicited resume. All unsolicited resumes sent to any Huntington Bank colleagues, directly or indirectly, will be considered Huntington Bank property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.</div>

GenAI Lead Data Scientist

William Blair & Company

<div></div><div><div><div>Solutions for Today's Challenges. Vision for Tomorrow's Opportunities.</div>
<div>
Join William Blair, the Premier Global Partnership.</div></div><div></div> 
We are hiring a Senior AI Engineer to join a newly formed AI Innovation Function, part of the Investment Banking AI &amp; Technology team. This is not a back-office engineering role. This role follows the Forward Deployed Engineer philosophy: you will not build in isolation. You will be embedded with deal teams and industry/sector groups, understanding their day-to-day workflows and delivering tools that create immediate, measurable impact on how they originate, execute, and close deals.

You will work across the full stack&mdash;data pipelines, ML models, LLM-powered applications, and Salesforce integrations&mdash;with a bias for shipping fast, learning from real user feedback, and iterating relentlessly.

RESPONSIBILITIES
<ul>
<li>Build AI-powered features and agents using Enterprise Claude and proprietary ML models, integrated directly into the Salesforce workflows bankers use every day.</li>
<li>Develop LLM applications for banking use cases including automated comparable analysis, buyer recommendation, meeting intelligence summarization, and deal status briefings.</li>
<li>Design and maintain data pipelines using Databricks and Dagster for feature engineering, model training, and real-time analytics.</li>
<li>Work directly with deal teams and industry groups to identify high-impact automation opportunities and translate banker pain points into working solutions.</li>
<li>Perform rapid prototyping and exploratory analysis&mdash;build proof-of-concept tools quickly to validate ideas before investing in production-grade implementations.</li>
<li>Integrate third-party AI tools (Rogo.ai, Blueflame AI, Fellow.ai) via APIs and ensure seamless data flows across the composable architecture.</li>
<li>Write well-tested, production-quality code with rigorous engineering practices: code reviews, CI/CD, monitoring, and documentation.</li>
<li>Contribute to the team's engineering standards and share knowledge as the team scales.</li>
</ul>
QUALIFICATIONS
<ul>
<li>3+ years of software engineering experience with full-stack capability and a track record of shipping production applications.</li>
<li>Experience building applications or agents using large language models: prompt engineering, RAG architectures, LLM orchestration, or tool-use patterns.</li>
<li>Experience building interconnected multi-agent ecosystems &mdash; implementing agent coordination, shared tooling, and communication patterns across autonomous components.</li>
<li>Solid ML fundamentals: ability to perform data analysis, build and evaluate models, and work with feature pipelines.</li>
<li>Rigorous engineering habits&mdash;you believe in tested code, clean architecture, and building for maintainability from the start.</li>
<li>Familiarity with capital markets; experience in or adjacent to investment banking, private equity, venture capital, or hedge funds is strongly preferred.</li>
<li>Experience with cloud platforms (Azure preferred), data tools (Databricks, Spark), and pipeline orchestration (Dagster, Airflow, or similar).</li>
<li>Outcome-focused mindset&mdash;you care about whether bankers actually use what you build and whether it moves the needle on their productivity.</li>
</ul>
PREFERRED QUALIFICATIONS
<ul>
<li>Experience in a Forward Deployed Engineer, solutions engineer, or embedded technical role with direct business stakeholder accountability.</li>
<li>Experience deploying multi-agent ecosystems into production environments &mdash; including operational monitoring, failure handling, and end-to-end lifecycle management.</li>
<li>Exposure to financial services workflows: deal execution, pitch preparation, due diligence, or financial modeling.</li>
<li>Experience working with Salesforce APIs or CRM platforms as integration surfaces.</li>
<li>A builder's mentality: you have side projects, open-source contributions, or a portfolio that demonstrates curiosity and initiative beyond your day job.</li>
</ul>
#LI-CH

#LI-Hybrid<div><div><h2 class="jobSectionHeader"> 
</h2>
<h2 class="jobSectionHeader">About Our Firm</h2> 


William Blair strives to attract qualified candidates who specialize in investment banking, investment management, private wealth management, and other strategic resource groups. We are committed to empowering our colleagues to deliver client success and engage in our communities. Our firm has delivered trusted advice for nine decades, continuing to deepen our expertise and relationships across asset classes and markets throughout North America, Europe, and Asia. We provide advisory services, strategies, and solutions to meet clients' evolving needs amid dynamic market conditions and varying industries. What sets us apart is that we are an independent partnership, with colleagues who have unique experiences, perspectives, and backgrounds. We empower our people to bring their best thinking so we can deliver the tailored, thoughtful work and problem-solving abilities that our clients expect. We invite you to learn more about us by visiting williamblair.com.

William Blair is an equal opportunity employer. It complies with all laws and regulations that prohibit discrimination in employment practice because of race, color, religion, creed, ancestry, marital status, gender, age, national origin, sexual orientation, unfavorable discharge from the military service or on the basis of a physical or mental disability that is unrelated to the employee's ability to perform the duties of the job applied for. EOE m/f/d/v

Be aware of hiring scams: William Blair has clear processes and guidelines with regards to recruiting. We do not request personal financial information in connection with an employment application nor does William Blair extend any employment offers without first conducting an interview through one of its registered offices. William Blair does not use instant messaging services such as WhatsApp, Telegram, or iMessage as part of the recruiting or interviewing process.

Note to External Recruiters / Search Firms: William Blair does not accept unsolicited resumes and will not pay for any placement resulting from the receipt of an unsolicited resume. Any unsolicited resumes received will not be considered as a valid submission.

Download William Blair's privacy policies for job applicants:
<ul>
<li>California Consumer Privacy Act Privacy Notice (CCPA)</li>
<li>General Data Protection Regulation Privacy Notice (GDPR)</li>
</ul>
Contact us should you have any questions or concerns.</div></div></div>

Lead Data Scientist – AI Engineer

Colorado Rockies

<div>
 Job Details
 
 
 
 Description
 
 
 
 Lead Data Scientist, Business Strategy &amp; Analytics
 
 
 
 About Us
 
 
 
 The Colorado Rockies Baseball Club is embracing the climb, committed to building a championship-caliber organization on the field, in the clubhouse, and throughout our business operations. Playing at altitude presents unique competitive challenges and opportunities, and we embrace innovation, collaboration, and evidence-based practices to support elite performance. Rooted in the traditions of America&rsquo;s pastime, we operate with integrity, service, quality, and trust while striving to create an exceptional experience for our players, staff, and fans.
 
 
 The Strategy &amp; Business Analytics team partners closely with leadership and functional departments to translate data into insight, insight into decisions, and decisions into measurable impact.
 
 
 
 Position Summary
 
 
 
 The Lead Data Scientist will play a foundational role in shaping and executing the Colorado Rockies&rsquo; business-focused advanced analytics and data science capability. This individual will be responsible for contributing to the organization&rsquo;s data strategy, identifying and prioritizing high-impact data science opportunities, and independently executing advanced analytical work&mdash;including predictive, prescriptive, and machine learning models.
 
 
 Reporting to the Chief Revenue &amp; Strategy Officer, the Lead Data Scientist will serve as a thought partner to leaders across the business, helping tackle complex challenges where traditional reporting is insufficient. While this role will initially have no direct reports, it is expected to play a critical role in shaping the organization&rsquo;s analytics capabilities. As the analytics needs of the business evolve, opportunities for increased scope and responsibility may emerge based on organizational needs and individual performance
 
 
 This role is best suited for a senior individual contributor who thrives on building robust, production-ready models that drive measurable business impact rather than purely exploratory analysis. It requires a combination of deep technical expertise, strong business acumen, and clear communication skills. The Lead Data Scientist must be comfortable working hands-on across the full analytics spectrum&mdash;from advanced modeling and experimentation to select foundational analysis where needed to accelerate capability development. Their input will help define the long-term vision, structure, and standards for business analytics at the Rockies.
 
 
 
 Essential Duties &amp; Responsibilities
 
 
 
 Advanced Analytics Execution
 
 
 <ul>
 <li>
 Design, develop, and deploy advanced analytical solutions &mdash; including predictive and prescriptive models &mdash; to address high-priority business questions across ticketing, marketing, pricing, fan engagement, partnerships, and operations.
 </li>
 <li>
 Apply statistical modeling, machine learning, optimization, experimentation, and forecasting techniques to improve decision quality and quantify risk, uncertainty, and upside.
 </li>
 <li>
 Translate complex analytical outputs into decision-ready insights and clear recommendations for senior leadership and non-technical stakeholders; document model assumptions and limitations to ensure appropriate application
 </li>
 <li>
 Own projects end-to-end, from problem framing and data exploration through modeling, validation, and deployment of tools &amp; insights into the business
 </li>
 <li>
 Establish monitoring metrics and standards to ensure models remain relevant as data and conditions evolve.
 
 
 </li>
 </ul>
 Operationalization &amp; Model Deployment
 
 
 <ul>
 <li>
 Develop production-ready data science solutions, including APIs, scoring pipelines, and system integrations, to embed predictive and prescriptive models directly into business workflows.
 </li>
 <li>
 Partner with IT, 601Analytics, and application owners to integrate models into CRM, pricing systems, marketing platforms, and other operational tools.
 </li>
 <li>
 Establish version control, testing, validation, and monitoring frameworks to ensure models perform reliably in production environments.
 
 
 </li>
 </ul>
 Business Partnership &amp; Project Prioritization
 
 
 <ul>
 <li>
 Partner with the Chief Revenue &amp; Strategy Officer and functional leaders to identify, scope, and prioritize data science initiatives aligned with organizational strategic priorities.
 </li>
 <li>
 Build credibility and trust with stakeholders by balancing analytical rigor with pragmatic business judgment.
 </li>
 <li>
 Work closely with Strategy and functional teammates to design and analyze experiments, test hypotheses, evaluate solution tradeoffs, and inform high-impact decisions.
 </li>
 <li>
 Collaborate with reporting and analytics partners across the organization to ensure alignment between advanced models, core metrics, dashboards, and decision
 
 
 </li>
 </ul>
 Foundational Analytics &amp; Capability Building (Initial Phase)
 
 
 <ul>
 <li>
 Maintain primary focus on advanced modeling, experimentation, and high-impact decision support while contributing selectively to foundational analysis during early capability development.
 </li>
 <li>
 Help establish best practices for documentation, reproducibility, data quality, and analytical rigor across projects.
 </li>
 <li>
 Partner to coach and develop analytics capabilities of existing teammates and to build functional leaders&rsquo; comfort leveraging data and analytics to lead their teams.
 
 
 </li>
 </ul>
 Data Strategy &amp; Analytics Vision
 
 
 <ul>
 <li>
 Contribute to the development of a long-term vision for business analytics at the Rockies, spanning advanced data science and scalable reporting and insight delivery capabilities.
 </li>
 <li>
 Partner closely with 601Analytics and internal data engineering resources to leverage a modern, scalable data warehouse environment, ensuring advanced models are built on reliable, well-governed data assets.
 </li>
 <li>
 Partner with IT and data engineering/architecture teams to ensure data science solutions are scalable, sustainable, and aligned with enterprise data strategy.
 </li>
 <li>
 Establish and adhere to documentation and file management standards to ensure tools and analyses can be efficiently maintained and evolved over time.
 </li>
 <li>
 Stay current with emerging techniques and data sources in data science, machine learning, and artificial intelligence, identifying opportunities to apply these tools aggressively yet responsibly&mdash;with appropriate governance, transparency, and risk management&mdash;to drive meaningful business impact.
 
 
 </li>
 </ul>
 Communication &amp; Leadership
 
 
 <ul>
 <li>
 Clearly communicate analytical findings through written, visual, and verbal formats tailored to technical and non-technical audiences.
 </li>
 <li>
 Exceptional problem-solving and critical-thinking skills, with the ability to connect analytical work to real business outcomes.
 </li>
 <li>
 Strong business acumen and curiosity about how organizations operate, generate revenue, and serve customers.
 </li>
 <li>
 Excellent communication skills, including the ability to explain complex concepts clearly and concisely to non-technical audiences.
 </li>
 <li>
 Proven ability to collaborate cross-functionally, manage competing priorities, and operate effectively in a fast-paced, evolving environment.
 </li>
 <li>
 Comfort working in ambiguity and helping design processes, standards, and structures where none previously existed.
 
 
 </li>
 </ul>
 
 Job Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Data Science, Statistics, Economics, Mathematics, Computer Science, Business Analytics, or a related quantitative field required.
 </li>
 <li>
 Master&rsquo;s degree or PhD preferred.
 </li>
 <li>
 7+ years of progressive experience in data science, advanced analytics, or a related analytical role within a business, sports, media, or consumer-facing environment.
 </li>
 <li>
 Experience with sports and entertainment, specifically with ticketing and pricing, is strongly preferred.
 </li>
 <li>
 Demonstrated experience independently leading complex, ambiguous analytical projects from concept through impact.
 </li>
 <li>
 Demonstrated experience influencing leaders through data-driven insights.
 </li>
 <li>
 Demonstrated knowledge of best practices around requirements gathering, analysis design, and storytelling through data visualization.
 </li>
 <li>
 Formal people management experience is not required, but experience coaching / developing the analytics skills of others is highly valued.
 
 
 </li>
 </ul>
 Technical Skills
 
 
 <ul>
 <li>
 Strong proficiency in Python and/or R for data analysis, modeling, and automation.
 </li>
 <li>
 Deep understanding of statistical methods, machine learning algorithms, forecasting, experimentation, and optimization techniques.
 </li>
 <li>
 Experience working with SQL and Snowflake / Databricks (or similar tools) to operate in cloud-based data science environments like MS Azure; comfort manipulating large, complex datasets.
 </li>
 <li>
 Experience building and deploying machine learning models into production environments (e.g., REST APIs, batch scoring systems, containerized services, or similar deployment patterns).
 </li>
 <li>
 Familiarity with data visualization and BI tools (e.g., Tableau, Power BI) and an understanding of how advanced models integrate into dashboards and decision workflows.
 </li>
 <li>
 Experience applying generative AI, LLMs, or agent-based systems to automate analysis, enhance insight generation, or augment business workflows in a responsible and production-ready manner.
 
 
 </li>
 </ul>
 WORKING CONDITIONS / WORK SCHEDULE
 
 
 <ul>
 <li>
 Work Environment: Full-time in office role.
 </li>
 <li>
 Work Hours: Full-time hours (typically Monday-Friday 8-5) with occasional extended hours during peak business periods or critical project milestones.
 </li>
 <li>
 Travel: Minimal, though occasional travel related to league meetings, vendors, or organizational events may be required.
 
 
 </li>
 </ul>
 
 Physical Job Requirements
 
 
 
 <ul>
 <li>
 This role operates in a professional office and stadium environment. Occasional exposure to crowd noise, outdoor weather conditions, and extended hours during homestands, promotional events, or special functions may be required.
 </li>
 <li>
 Must be able to remain in a stationary position for extended periods (e.g., sitting at a desk, attending meetings).
 </li>
 <li>
 Occasionally moves about the office, stadium, and event spaces to access equipment, vendors, and staff.
 </li>
 <li>
 Frequently communicates via phone, video conference, and in person; must be able to exchange accurate information.
 </li>
 <li>
 Ability to lift up to 15 pounds occasionally (e.g., promotional materials, laptop bag).
 
 
 </li>
 </ul>
 
 Compensation &amp; Benefits
 
 
 
 <ul>
 <li>
 Annual Salary Range: $125,000 - $145,000. This is a regular-status, full-time, Non-Exempt position.
 </li>
 <li>
 As a candidate for this position, your salary and related elements of compensation will be contingent upon your work experience, education, job-related skills, and any other factors the Colorado Rockies consider relevant to the hiring decision for this position.
 </li>
 <li>
 In addition to the base salary, the Club believes in providing a very competitive and generous compensation and benefits package for its employees. Benefits include but are not limited to Medical, Dental, Vision, 401(k) with employer match, generous vacation and holiday program, employee parking, employer-provided game tickets to home games, onsite fitness classes and experiences, employee discounts on merchandise, and so much more! All benefits are subject to eligibility requirements and the terms of official plan documents, which may be modified or amended at any given time.
 
 
 </li>
 </ul>
 
 Application Process
 
 
 
 <ul>
 <li>
 Applications will be reviewed on a rolling basis but must be received by March 25th.
 </li>
 <li>
 The estimated time to complete the recruitment process will be by May 22nd.
 </li>
 <li>
 Please note this is just an estimate, and the recruiting process may be extended to removed at any time.
 </li>
 <li>
 For current Colorado Rockies employees:
 </li>
 <ul>
 <li>
 Apply via the internal job board in UKG by following these prompts: MENU &gt; MYSELF &gt; VIEW OPPORTUNITIES &gt; select the position &gt; CONSENT &gt; APPLY NOW.
 </li>
 <li>
 If you are unable to access UKG, please list your most recent Manager as an Employee Reference on your application.
 
 </li>
 </ul>
 </ul>
 
 Equal Opportunity Employer
 
 
 
 Rockies baseball is for everyone! We pride ourselves on hiring, developing, and promoting talent as an Equal Employment Opportunity Employer. All qualified applicants and employees will receive consideration for employment or promotion without regard to race (including, but not limited to, traits historically associated with race, such as hair texture and length and/or protective hairstyles), color, national origin, gender identity, gender expression, sexual orientation, familial status, marital status, ancestry age (40+), creed, religion, disability, veteran status, pregnancy/childbirth and related conditions, or any other category or activity protected by law. In addition, we will endeavor to provide reasonable accommodation to otherwise qualified job applicants and employees with known physical or mental disabilities in compliance with the ADA. All employment and promotion decisions will be decided on the basis of qualifications, merit, and business needs.
</div>

Lead Data Scientist, Business Strategy & Analytics

Starbucks

<div>Now Brewing &ndash; Lead Data Scientist! #tobeapartner
From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
As a Lead Data Scientist on the Global Supply Chain Data Science team, you will lead the development of advanced forecasting models and optimization algorithms that shape supply chain and inventory decisions. Your work will directly impact coffeehouses, transportation, distribution centers, and suppliers at scale. 
As a lead data scientist, you will&hellip;<ul><li> Own the end-to-end lifecycle of AI/ML solutions, from ideation and prototyping to production deployment, ensuring robust offline evaluation and real-time performance monitoring.</li><li> Work closely with product and internal users. You will understand business initiatives, challenges, questions, and transform user requirements into technical solutions.</li><li> Contribute to project planning, and assist the team with estimations, timelines, and prioritization. Assists in developing the analytical roadmap, data, and technology strategy.</li></ul> 
Mentor and Develop Talent<ul><li> Guide data scientists and senior data scientists in advanced analytics, optimization techniques, and business impact storytelling.</li><li> Foster a culture of innovation and continuous improvement within the data science organization.</li></ul> 

We&rsquo;d love to hear from people with:<ul><li> 
 Education: Bachelors Degree with a concentration in a quantitative discipline. Masters preferred</li><li> 5+ years of progressive experience in data science, with a proven track record of end-to-end data product and model deployment that delivers measurable business impact.</li><li> 5+ years of experience in machine learning and statistical techniques, including regression, classification, clustering, and causal inference.</li><li> Advanced proficiency in Python, SQL, and cloud-based analytics platforms (e.g., Databricks, Azure), with experience developing production-grade data pipelines and model outputs.</li><li> Excellent communication and data storytelling skills, with the ability to translate complex methodologies into clear, actionable insights. Translate business challenges into research questions, and present findings to technical and non-technical audiences</li><li> Experience building in-house production systems in complex and data-rich domains.</li><li> Mentoring experience</li></ul> 
Preferred Skills:<ul><li> Experience in building forecasting models for time series or operational planning</li><li> Experience in optimization techniques such as linear programming, mixed-integer programming, or heuristic algorithms for decision support</li><li> Background with PySpark and Databricks for distributed data processing and scalable analytics in cloud environments</li><li> Advanced degree (MSc or PhD) in Statistics, Operations Research, Applied Mathematics, or related quantitative field.</li></ul> 
As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools. Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor&rsquo;s degree through Arizona State University&rsquo;s online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities. You will also have access to backup care and DACA reimbursement. Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. For additional information regarding partner perks and more detailed information about benefits, go to starbucksbenefits.com.<ul><li>If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above.</li></ul> 
The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. At Starbucks, it is not typical for an individual to be hired at the high end of the range for their role, and compensation decisions are dependent upon the facts and circumstances of each position and candidate. 
We believe we do our best work when we're together, which is why we're onsite four days a week.
Join us and inspire with every cup. Apply today!
Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law.
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances. 
 
Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation@starbucks.com or 1(888) 611-2258.</div>

lead data scientist - Data & Analytics (Seattle, WA)

Wells Fargo

<div>About this role:
Wells Fargo is seeking Lead Gen AI Data Scientist role as part of the Consumer Model Development. This role is pivotal in leading the development and implementation of cutting-edge Generative AI (GenAI) and Natural Language Processing (NLP) solutions within the Consumer LOB's - Banking, Lending, and WIM divisions. The successful candidate will lead model development for projects/programs and guide a team of data scientists and collaborate with business and technology partners to drive end-to-end solution design and development for implementing virtual assistants, content generation, agentic frameworks, and others for improving employee/customer experience, driving operational efficiencies, and mitigating risks. Learn more about the career areas and lines of business at wellsfargojobs.com.
In this role, you will:<ul><li>
Lead the design, development, and deployment of GenAI and NLP models for various consumer-facing applications</li><li>
Translate business problems into technical solutions, leveraging advanced GenAI/NLP/ML methodologies</li><li>
Collaborate with cross-functional teams to integrate AI solutions into business processes, ensuring scalability and robustness</li><li>
Provide mentorship and technical guidance to junior data scientists</li><li>
Engage with business stakeholders to communicate insights, model outcomes, and the strategic value of AI initiatives</li><li>
Ensure compliance with regulatory requirements and internal risk management policies</li></ul>
Required Qualifications:<ul><li>
5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education</li><li>
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science</li></ul>
Desired Qualifications:<ul><li>
Demonstrated expertise in Generative AI, including large language models, Generative AI frameworks, and advanced NLP techniques which includes leading GenAI projects from conception to production
</li><li>Proficiency in Python, PySpark, TensorFlow, PyTorch, and cloud platforms such as Google Cloud Platform (GCP) or Vertex AI</li><li>
Strong background in GenAi/NLP, machine learning, deep learning, and statistical analysis 
Experience in the financial services industry, particularly within consumer banking, lending, wealth and asset management</li></ul><ul><li>
Familiarity with regulatory and compliance considerations in AI model deployment</li><li>
Strong communication and presentation skills with the ability to translate complex technical concepts to non-technical stakeholders</li><li>
Strong full stack data science skills</li><li>
A track record of published research or patents in AI/ML</li></ul>
Job Expectations:<ul><li>
Ability to travel up to 10% of the time</li><li>
This position will require onsite presence at one of the locations listed below in a hybrid work schedule</li><li>
This role is not eligible for Visa sponsorship</li></ul>
Posting Location(s):
<ul><li>401 S Tryon St &ndash; Charlotte, North Carolina, 28202</li><li>
150 E 42nd St. &ndash; New York, New York 10017</li></ul>
Pay Range:
New York, NY Pay Range $191,000.00 - $305,000.00<ul><li>
May be considered for a discretionary bonus, Restricted Share Rights, or other long-term incentive awards</li><li>
Actual salary is determined by location, experience and qualifications of the job</li></ul></div>

Lead GenAI Data Scientist

Intuit

<div><h2 class="jobSectionHeader">Overview</h2>
Come join the Consumer Group (CG) AI Team as a Principal AI Scientist. The CG AI team focuses on bringing the top-notch AI features to Intuit&rsquo;s TurboTax customers for their delight. You will get the chance to lead the work to leverage the cutting-edge AI technologies, as well as collaborate across organizations and functions with our partners in the engineering, product management, analytics and design departments to ensure that we are building a pleasant customer experience, striving for more money, less work and complete confidence for our TurboTax customers. 
Responsibilities<ul><li>
Practices leadership and communication skills to influence teams and to evangelize data science across the organization</li><li>
Collaborates with stakeholders to define success criteria and align model metrics with business goals. Works side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products</li><li>
Leads technical work of a scrum team: initiating and designing model solutions, driving end-to-end architecture designs of the team&rsquo;s work, and holding the team accountable for high quality code, git, design, costs and implementation standards</li><li>
Performs hands-on data analysis and modeling with large data sets, including discovering data sources, getting data access, cleaning up data, and making them &ldquo;model-ready&rdquo;. You need to be willing and able to do your own ETL and design/build featurization.</li><li>
Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.</li><li>
Communicates with partners to ensure successful delivery and integration of DS solutions.</li><li>
Proactively researches, explores, and enables new ML technologies. Keeps up with the new developments in academia and industry and considers possible extensions to solve Intuit customer problems.</li></ul><div></div> 
Qualifications<ul><li>
10+ years of industry experience with data science</li><li>
BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent experience</li><li>
8+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement or Deep Learning.</li><li>
Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.</li><li>
Proficient in NLP techniques, Explainable AI, and ML frameworks.</li><li>
Expertise in modern advanced analytical tools and programming languages such as Python, Scala, Java and/or R.</li><li>
Experience with building end-to-end reusable pipelines from data acquisition to model output delivery</li><li>
Quick learner, adaptable, with the ability to work independently in a fast-paced environment</li><li>
Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users</li></ul> 
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:<div> 
Bay Area California: $260,500 - 352,500 
Southern California: $237,000 - 320,500</div></div>

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