The Data And AI Podcast

To Apply for this Job Click Here

About the Job

Role Title: Supply Chain Planning Leader

Compensation: Competitive base salary + annual incentive

Location: Dallas, TX

The Opportunity

We’re partnering exclusively with a large, global manufacturing organization to hire a senior leader who will own enterprise planning and demand generation at scale. The business is entering a period of sustained growth and investment, creating a need to fundamentally modernize how demand, supply, inventory, and manufacturing capacity are planned and connected.

This is a rare opportunity to step into a highly influential role where planning is treated as a strategic capability, not a back‑office function. You’ll act as the enterprise owner for planning-defining the vision, shaping the systems, and driving execution across a complex, global footprint.

If you are motivated by scale, transformation, and real operational impact, this role offers the chance to shape how an entire organization plans, builds, and grows.

About the Role

The organization is looking for a senior planning leader who can operate across two equally important dimensions. The first is enterprise planning ownership: demand planning, inventory optimization, supply planning enablement, and manufacturing capacity planning. The second is transformation leadership: modernizing planning processes, platforms, data, and ways of working.

This is not a purely strategic or people‑management role. You’ll be expected to remain technically fluent, challenge system and architecture decisions, and stay close to execution. You will lead through a “leader of leaders” model while setting the technical and analytical direction for planning across the enterprise.

You’ll partner deeply with manufacturing, supply chain, finance, and technology teams to ensure demand signals are actionable, realistic, and aligned with what can actually be produced-both now and as capacity scales over time.

What You’ll Be Doing

Own end‑to‑end enterprise planning, spanning demand planning, inventory optimization, supply planning, and capacity planning

Generate high‑quality demand signals that drive inventory strategy, supply plans, and long‑term manufacturing investment

Ensure tight alignment between demand, supply planning, manufacturing operations, and financial plans

Define and own the planning technology vision, architecture, and multi‑year roadmap

Lead transformation initiatives leveraging modern planning platforms, advanced analytics, automation, and AI/ML capabilities

Drive legacy planning system modernization and ERP‑integrated planning transformations

Partner closely with manufacturing to support factory start plans, scenario planning, and footprint expansion

Interpret large, complex datasets to identify trends and guide enterprise decision‑making

Lead change management, communication, training, and adoption efforts across global planning teams

Develop and mentor senior leaders, establish consistent processes, and define future skill requirements for the planning organization

What They’re Looking For

Significant experience leading enterprise‑scale planning or supply chain transformation initiatives

Deep expertise across demand planning, supply planning, inventory optimization, and manufacturing capacity planning

Proven track record delivering modern planning systems and migrating from legacy platforms

Strong technical fluency with planning technologies, analytics, and data‑driven decision frameworks

Experience operating in complex, global manufacturing environments

Demonstrated success leading managers and senior leaders in distributed, global teams

Ability to operate hands‑on while setting long‑term strategic direction

Comfortable owning ambiguous, high‑impact problems and seeing them through end‑to‑end

Nice to Have

Background in highly technical or capital‑intensive manufacturing environments

Exposure to advanced analytics, automation, AI, or machine‑learning‑enabled planning

Experience supporting large‑scale manufacturing expansion or capacity growth programs

Strong change‑management instincts and experience driving adoption at scale

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior AI Engineer

Locations: San Francisco, CA Work Arrangement: 4-5 days per week onsite (In-person collaboration focus) Compensation: $425,000 – $600,000 Total Cash (Base + ~50% Performance Bonus)

The Opportunity

Our client is a premier global technology investment firm with a 26-year track record of excellence and over 200 employees. Despite their scale, they maintain a flat, entrepreneurial, and “deeply technical” culture.

They are currently seeking a Senior AI Engineer(VP Level) to help lead a digital transformation. This is not a “maintenance” role; you will be tasked with reimagining the future of private equity. You will build the AI agents and autonomous workflows that will automate and augment the high-volume analytical work currently performed by investment professionals.

Note: This role does not support sponsorship’s

The Mission

Your goal is to move the firm beyond legacy workflows (Excel, email, and PowerPoint) and toward an AI-augmented investment process.

• Focus: Building production-grade agentic systems and AI applications that drive business value.

• Philosophy: Our client is not training foundational models from scratch. Instead, you will use off-the-shelf models (OpenAI, Anthropic, etc.) and focus on sophisticated orchestration, RAG systems, and workflow integration.

• Impact: You will identify repetitive, associate-level tasks and build systems where AI performs 80% of the heavy lifting, allowing humans to focus on high-level refining and decision-making.

Key Responsibilities

• Architect & Build: Design and deploy AI-powered systems and agent-based frameworks into production.

• Integrate: Develop the architecture to connect LLMs with diverse data sources, including AWS, Snowflake, Salesforce, and external alternative datasets (market research, web traffic, etc.).

• Collaborate: Work directly with Investment Partners and Operating Teams to translate complex investment processes into automated AI workflows.

• Innovate: Serve as a technical leader in deciding when to use single vs. multi-agent systems and selecting the appropriate LLM for specific use cases.

Candidate Profile

We are looking for a builder, not a maintainer. The ideal candidate likely comes from a high-growth startup environment (Series A-C) or a specialized internal product team.

Technical Requirements

• Foundation: 5-10 years of professional experience, including at least 4+ years of core software engineering.

• AI Pivot: A deliberate focus over the last 2-4 years on Generative AI and LLM application design.

• Stack: Mastery of Python and Cloud Infrastructure (AWS preferred).

• Data Savvy: Experience with Snowflake and modern data pipelines (Fivetran, etc.). Exposure to financial data (EBITDA, market data) is a significant plus.

Soft Skills & Mindset

• Entrepreneurial: You thrive in a flat organization where you are expected to take ownership and manage your own work.

• “Code-Switcher”: Ability to communicate technical architecture to engineers while explaining business value to Senior Investment Partners.

• Practicality: You prioritize shipping functional, high-impact tools over theoretical or academic exercises.

Why Join?

• High Visibility: This role is integrated into the investment team; you will interact with firm leadership daily.

• Modern Tools: The team is already leveraging AI-assisted coding (Claude Code) and modern data stacks to move fast.

To Apply for this Job Click Here

To Apply for this Job Click Here

The Company
We’re partnered with a fast-growing, product-led SaaS company where data plays a central role in product decision-making. The data team works closely with senior leadership and is continuing to scale.

The Role
This is a Staff-level individual contributor role within the Product Analytics team, focused on owning and scaling the company’s experimentation framework.

The organization is continuing to build its experimentation maturity, and this hire will play a key role in strengthening both the technical implementation and adoption of experimentation across the business.

You will act as a technical anchor for the team, ensuring robust statistical practices while working closely with stakeholders to support data-informed product decisions.

Key Responsibilities

• Own and scale the experimentation roadmap across product teams
• Design and implement robust experimentation frameworks (e.g., Bayesian methods, sequential testing)
• Apply causal inference to user behavior, feature adoption, retention, and churn
• Partner with product and engineering teams to ensure experiments are correctly designed and implemented
• Provide guidance to team members on advanced statistical methods
• Work with stakeholders to support adoption of experimentation best practices
• Evaluate and support implementation of experimentation tooling

Requirements

• 6+ years of experience in Data Science or Product Analytics
• Strong experience with experimentation (A/B testing, Bayesian methods, or similar approaches)
• Solid understanding of causal inference
• Experience working in SaaS product environments
• Ability to work with a high level of ownership and collaborate effectively with stakeholders

Technical Skills

• Python
• SQL
• Experience working in shared code environments (e.g., GitHub)

Nice to Have

• Experience evaluating or implementing experimentation platforms
• Exposure to modern AI-assisted tools (e.g., Cursor, Claude Code)

Additional Information

• Opportunity to contribute to the development of experimentation practices within a growing product organization
• High-visibility role with direct impact on product decision-making
• Fully remote within the US, aligned to EST working hours

Eligibility
Applicants must have the right to work in the United States. Sponsorship is not available.

To Apply for this Job Click Here

To Apply for this Job Click Here

Role Title: Staff Data Scientist, Go-To-Market

Compensation: $180,000 – $210,000 USD Base

Location: United States (Remote)

The Opportunity

We’re partnering exclusively with a fast‑growing B2B SaaS company to hire a Staff Data Scientist who will play a central role in shaping how data drives customer growth, retention, and revenue strategy. The business is at an inflection point, intentionally moving from descriptive analytics toward predictive, model‑driven decision making across its go‑to‑market organization.

This is a rare opportunity to step into a high‑impact, senior individual contributor role where the models you build directly influence how teams prioritize accounts, engage customers, and allocate resources.

About the Role

The team is looking for a Staff Data Scientist who can operate across two complementary problem spaces. The first is predictive customer analytics: building robust models for churn, retention, expansion, and early‑lifecycle lifetime value. The second is stakeholder‑embedded problem solving: translating ambiguous commercial questions into scalable data science solutions that teams actually use.

This role is intentionally hands‑on and model‑heavy. You’ll own work from problem framing and feature discovery through model development, validation, and production handoff. While you won’t manage people, you’ll be expected to lead technically, mentor teammates, and help set the standard for applied data science. This is a US‑remote role with regular collaboration across commercial teams.

What You’ll Be Doing

• Design, build, and iterate on predictive models for customer churn, retention, and expansion
• Develop early‑signal frameworks to estimate customer lifetime value well before traditional cohort analysis
• Build customer segmentation models that inform prioritization and targeting across go‑to‑market teams
• Partner closely with Customer Success, Account Management, and Marketing to translate ambiguous questions into modeling solutions
• Incorporate uplift and attribution concepts to connect customer actions and interactions to expected outcomes
• Validate model performance, monitor outcomes, and continuously improve prediction quality
• Collaborate with data engineering to support batch deployment and operationalization of models
• Mentor analysts and peers on modeling approaches, feature engineering, and best practices

What They’re Looking For

• 6+ years of experience in data science with ownership over impactful machine learning projects
• Strong experience building models for churn, retention, customer lifetime value, or segmentation
• Advanced proficiency in Python and SQL
• Demonstrated experience deploying machine learning models into production or operational workflows
• Solid understanding of B2B SaaS business models and sales cycles
• Ability to communicate complex model outputs clearly to non‑technical stakeholders
• Proven ability to operate independently, owning problems end‑to‑end in ambiguous environments

Nice to Have

• Exposure to analytical engineering or ML production architecture
• Experience working alongside data engineering teams on model deployment
• Familiarity with causal inference or marketing effectiveness modeling
• Comfort using modern developer tooling to accelerate modeling workflows

• Seniority Level

  Mid-Senior level

• Industry

  • Software Development
  • IT Services and IT Consulting

• Employment Type

  Full-time

• Job Functions

  • Engineering
  • Information Technology

• Skills

  • Data Science
  • Statistics
  • Machine Learning
  • Java
  • Software Development
  • Data Analytics
  • Data Analysis
  • Analytics
  • SQL
  • Algorithms
  • Python (Programming La

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Analytic Engineer (Remote – U.S.) | Up to $200K + Bonus

If you’re someone who lives in SQL, loves building clean data models, and actually cares about making data usable-this is worth a look.

We’re hiring a Senior Analytic Engineer to own the transformation layer of a modern data stack. This isn’t a dash-boarding role-this is about building the foundation that powers decision-making across the business.

What you’ll be doing:

• Modeling clean, scalable datasets with dbt
• Writing advanced SQL (CTEs, window functions, performance tuning)
• Working across Snowflake / BigQuery / Redshift
• Defining core business metrics (and making sure everyone trusts them)
• Orchestrating pipelines (Airflow / MWAA)
• Using Python for automation and data workflows

What we’re looking for:

• 5+ years in analytic engineering / data engineering
• Deep SQL expertise
• Strong dbt experience
• Solid understanding of dimensional modeling & data warehousing
• Experience in modern cloud data environments
• Deep understanding of dimensional modeling, data warehouse design patterns, and analytical best practices
• Experience working with SaaS metrics (MRR, churn, customer lifetime value, etc.)
• Proficiency with GitHub for version control and collaborative development
• Strong communication skills with ability to translate technical concepts for business stakeholders

Details:

• 100% Remote (U.S. only)
• Must be able to work in the US without sponsorship
• Up to $200K base + bonus

This is a high-ownership, high-impact role where you’ll help shape how data is modelled, defined, and trusted across the company.

If you’re interested (or know someone who is), drop a comment or DM me.

To Apply for this Job Click Here

To Apply for this Job Click Here

Title: Senior Data Engineer

Location: Remote (Must be based in EST/CST)

Pay: $150K-$180K + Equity

Overview:

An emerging AI-driven technology company is seeking a Senior Data Engineer to own and operate the data infrastructure that powers their core products. This organization builds advanced systems enabling real‑time decisioning, predictive analytics, and large‑scale data processing for enterprise clients. This role blends backend engineering, cloud infrastructure, and data platform development building highly scalable systems end to end.

Responsibilities:

• Design, build, and operate production data services and APIs in a cloud environment using containerized applications
• Implement and scale vector search capabilities supporting high‑volume similarity retrieval across 50M+ records
• Build and optimize data pipelines and ETL/ELT workflows using Python, SQL, and Databricks
• Architect cost‑effective cloud infrastructure supporting real‑time and batch workloads
• Collaborate cross‑functionally with data science and product teams to translate requirements into scalable solutions
• Own monitoring, observability, and service reliability for key data‑driven systems
• Improve internal tooling, infrastructure components, and engineering best practices

Must-Have Qualifications:

• 5+ years in data engineering, backend engineering, or platform infrastructure roles
• Strong hands‑on experience with AWS (EKS, S3, RDS, Lambda, IAM, SQS/SNS)
• Proficiency deploying and troubleshooting containerized applications on Kubernetes
• Production-grade Python and SQL experience
• Hands-on experience with Databricks (Delta Lake, Jobs, Workflows)
• Experience working with vector databases or vector search technologies (Milvus, Databricks Vector Index)
• Familiarity with CI/CD, Docker, Helm, and infrastructure-as-code (Terraform or CloudFormation)

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff Data Scientist

Location: New York City (Hybrid)

Compensation: Up to $250,000 base + bonus + equity

Company Overview

A high-growth consumer fintech and e-commerce platform is building the credit infrastructure powering digital commerce in a large, underserved market. The business has reached profitability, processes hundreds of millions in annual transaction volume, and continues to scale rapidly with strong backing from top-tier investors.

The team is lean, highly technical, and composed of leaders from globally recognized technology and marketplace companies. This is an opportunity to join at a pivotal stage and directly influence core revenue-driving systems.

The Role

As a Staff Data Scientist, you will play a critical role in developing and deploying machine learning models that directly impact the company’s P&L. You’ll work across credit risk, pricing, and marketplace optimization problems, owning the full lifecycle from problem definition through to production.

This is a highly cross-functional role partnering with engineering, product, and leadership to drive data-informed decisions and scalable modeling solutions.

Key Responsibilities

• Build and deploy machine learning models for underwriting, credit risk, and portfolio optimization
• Develop pricing, ranking, and personalization algorithms to improve marketplace performance
• Apply causal inference and experimentation techniques to optimize decision-making
• Own projects end-to-end: from exploratory analysis and modeling through to production deployment
• Translate complex modeling outputs into clear business insights and recommendations
• Collaborate closely with engineering and product teams to operationalize models

Requirements

• 5+ years of experience in data science or machine learning in a production environment
• Strong foundation in statistical modeling and machine learning (e.g., classification, ensemble methods)
• Experience deploying models into production and iterating based on real-world performance
• Proficiency in Python and SQL
• Experience with experimentation, causal inference, or uplift modeling
• Strong problem-solving skills with the ability to operate in ambiguous, fast-paced environments

Preferred Background

• Advanced degree (PhD or Master’s) in a quantitative field such as Statistics, Mathematics, Economics, or Operations Research
• Experience in fintech, lending, or credit risk modeling
• Exposure to marketplace, pricing, or recommendation systems
• Familiarity with optimization techniques and constrained modeling problems

What Makes This Opportunity Unique

• Direct ownership of models that impact revenue and risk
• High visibility role working closely with senior leadership
• Fast-paced, startup environment with significant autonomy
• Opportunity to shape core data science strategy and systems

• If you’re excited by building high-impact machine learning systems in a fast-moving environment and want to see your work directly drive business outcomes, this is a unique opportunity to do so at scale.

To Apply for this Job Click Here