Mid Level Data Science Analyst Jobs
Mid level data science analyst jobs go to analysts ready to own projects end to end, translate findings into business decisions, and guide junior teammates without needing close oversight. Openings are concentrated across Technology & Software, Retail, and Consulting & Professional Services, with a strong share of remote and hybrid work available, and employers like Capital One, Walmart, and ZS hiring at this level now.
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About AllTrails
AllTrails is the app for exploring the outdoors. We help people spend more time outside by connecting them to their next adventure. Home to the world’s largest outdoor community, with members and trails around the globe, you can find AllTrails in the Apple App Store, Google Play Store, and at alltrails.com. Every day, our team works to get more people outside and help our members have better experiences on the trail. We lead with our values—positivity, innovation, humility, adaptability, inclusivity, and stewardship—in everything we do. Join us! This is a U.S. based remote position. While this role does not require in-person attendance, we have a strong preference for candidates based in or near one of these cities: San Francisco CA, Portland OR, Seattle WA, Denver CO, and New York NY. Being in one of these cities creates opportunities to connect with teammates through Trail Days, co-working sessions, and local gatherings while still having the flexibility to work remotely. San Francisco employees are highly encouraged to come to the office one day per week.
About The Role
Reporting to the Director of Engineering, Maps & Data, this role will lead the AllTrails’ Data Science & Engineering team, a small and centralized engineering function that cross-functionally supports the business across product pods and partner teams including: data analytics, finance, and marketing. The team’s scope spans scalable data infrastructure, data governance, reliability, compliance, and the development and productionization of machine learning, AI, and algorithmic solutions that power internal operations and member-facing product experiences.
Due to high candidate volume and to ensure our hiring team has sufficient time to give every application the attention it deserves, we have set a closing date of August 20th for this position.
What you'll be doing
Team Leadership & People Management
- Manage & Grow the Team: Lead, hire, and coach a team of data engineers and applied data scientists while fostering team health, professional development, and high performance through active coaching and performance management.
Strategic Business Partnership & AI Strategy
- Stakeholder Alignment: Partner with cross-functional leaders to translate business needs into technical requirements, prioritize initiatives, and balance long-term platform investments with near-term delivery goals.
- Domain & AI Innovation: Serve as a key thought partner on leveraging data, AI, and automation to enhance AllTrails' internal productivity, trail content, map quality, and member personalization experiences.
Data Platform & Engineering Execution
- Pipeline & ML Architecture: Drive the architecture and delivery of scalable batch and streaming pipelines, while scaling the productionization of ML models and algorithmic systems into dependable engineering solutions.
- System Operations & Reliability: Oversee orchestration, transformation, alerting, and data flow across the organization—troubleshooting complex performance bottlenecks and system failures to ensure high system uptime.
Data Governance, Democratization & Platform Operations
- Governance & Self-Service: Champion data reliability, quality, privacy, compliance, and cost efficiency while building tools for data cataloging, documentation, and self-service to democratize data assets.
- Velocity & Continuous Improvement: Create organizational leverage by improving time-to-insight, debugging speed, and deployment velocity, while continuously evaluating new tools and technologies to elevate data capabilities.
What You Bring
Team & People Leadership
- Leadership Experience: 5+ years in data engineering with 3+ years managing data engineering, machine learning, and data science teams with a focus on coaching senior ICs, career development, and building an inclusive, accountable team culture.
- Working Style & Values: An adaptable, self-motivated leader who thrives in fast-paced, ambiguous environments—balancing strategic vision with hands-on technical guidance, humility, empathy, and a passion for the outdoors.
Technical Architecture & Infrastructure
- Platform & Governance: Hands-on experience managing GCP data infrastructure, enforcing data governance, and maintaining production-grade data access patterns, storage, caching, and optimization standards.
- Modern Data Stack: Extensive proficiency in transforming high-volume datasets in columnar SQL warehouses (BigQuery preferred, or Snowflake) using ELT tools (Dataform, dbt) and orchestrators like Apache Airflow.
- Pipeline & Processing: Proven expertise designing complex SQL/Python pipelines using parallelized processing frameworks (Dataflow, Spark, or similar) and core data modeling techniques (dimensional, star schema).
Engineering Practices & AI/ML Ops
- DevOps & SDLC: Deep familiarity with software engineering best practices, including Docker/Kubernetes, CI/CD pipelines, monitoring/observability tools (Datadog, New Relic, etc.), code reviews, and monthly on-call rotation.
- Applied AI/ML: Track record of guiding teams through the full ML lifecycle (MLOps) to support applied use cases like recommendation, ranking, personalization, and classification engines.
Stakeholder Management & Execution
- Cross-Functional Ownership: Skilled at leading across both platform foundations and applied data products, with the business judgment to prioritize competing stakeholder needs.
- End-to-End Delivery: Proven ability to translate complex business requirements into technical specs, collaborating effectively with stakeholders to own projects from inception to completion.
Bonus Points
- Experience working with geospatial data, maps, tiling, graph databases, and/or routing
- Experience working in a multi-cloud environment (GCP + AWS)
- Experience working at a B2C company
- Skilled at managing infrastructure as code (e.g. Terraform)
Perks & Benefits
- Competitive and equitable compensation, including ownership through equity and performance-based bonuses
- Comprehensive health, dental, and vision coverage to support your physical and mental well-being
- Unlimited PTO in addition to company holidays
- Dedicated time once a month to test and improve our product through company-wide no-meeting days
- Fully paid parental leave to birthing and non-birthing parents
- 401k Match & access to financial wellness resources through Origin
- Remote work stipend to help you design a comfortable and productive home office
- Annual learning stipend to invest in your long-term professional growth and skills
- Exclusive discounts on our subscriptions and merchandise for you and your friends & family
- An authentic investment in you as a human being and a professional—we value your identity as much as your output
Nature celebrates you just the way you are and so do we! At AllTrails we’re passionate about nurturing an inclusive workplace that values diversity. It’s no secret that companies that are diverse in background, age, gender identity, race, sexual orientation, physical or mental ability, ethnicity, and perspective are proven to be more successful. We’re focused on creating an environment where everyone can do their best work and thrive.
Offers of employment are contingent upon the successful completion of a background check. AllTrails will consider all qualified applicants, including those with arrest and conviction records, in a manner consistent with all applicable laws, including the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York City Fair Chance Act. AllTrails participates in the E-Verify program for all remote locations.
By submitting my application, I acknowledge and agree to AllTrails' Job Applicant Privacy Notice. All official recruiting communications from AllTrails will come from an name@alltrails.com email address. Please review sender details carefully, and do not engage with anyone asking for payment or sensitive financial information as part of the hiring process.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.
This range represents our good faith estimate for a successful candidate’s starting base salary. Final offers are determined by a blend of factors including specialized skills, experience, and relevant credentials. In addition to base pay, our total rewards package includes an equity stake in the company and a performance-based bonus program.
About AllTrails
AllTrails is the app for exploring the outdoors. We help people spend more time outside by connecting them to their next adventure. Home to the world’s largest outdoor community, with members and trails around the globe, you can find AllTrails in the Apple App Store, Google Play Store, and at alltrails.com. Every day, our team works to get more people outside and help our members have better experiences on the trail. We lead with our values—positivity, innovation, humility, adaptability, inclusivity, and stewardship—in everything we do. Join us! This is a U.S. based remote position. While this role does not require in-person attendance, we have a strong preference for candidates based in or near one of these cities: San Francisco CA, Portland OR, Seattle WA, Denver CO, and New York NY. Being in one of these cities creates opportunities to connect with teammates through Trail Days, co-working sessions, and local gatherings while still having the flexibility to work remotely. San Francisco employees are highly encouraged to come to the office one day per week.
About The Role
Reporting to the Director of Engineering, Maps & Data, this role will lead the AllTrails’ Data Science & Engineering team, a small and centralized engineering function that cross-functionally supports the business across product pods and partner teams including: data analytics, finance, and marketing. The team’s scope spans scalable data infrastructure, data governance, reliability, compliance, and the development and productionization of machine learning, AI, and algorithmic solutions that power internal operations and member-facing product experiences.
Due to high candidate volume and to ensure our hiring team has sufficient time to give every application the attention it deserves, we have set a closing date of August 20th for this position.
What you'll be doing
Team Leadership & People Management
- Manage & Grow the Team: Lead, hire, and coach a team of data engineers and applied data scientists while fostering team health, professional development, and high performance through active coaching and performance management.
Strategic Business Partnership & AI Strategy
- Stakeholder Alignment: Partner with cross-functional leaders to translate business needs into technical requirements, prioritize initiatives, and balance long-term platform investments with near-term delivery goals.
- Domain & AI Innovation: Serve as a key thought partner on leveraging data, AI, and automation to enhance AllTrails' internal productivity, trail content, map quality, and member personalization experiences.
Data Platform & Engineering Execution
- Pipeline & ML Architecture: Drive the architecture and delivery of scalable batch and streaming pipelines, while scaling the productionization of ML models and algorithmic systems into dependable engineering solutions.
- System Operations & Reliability: Oversee orchestration, transformation, alerting, and data flow across the organization—troubleshooting complex performance bottlenecks and system failures to ensure high system uptime.
Data Governance, Democratization & Platform Operations
- Governance & Self-Service: Champion data reliability, quality, privacy, compliance, and cost efficiency while building tools for data cataloging, documentation, and self-service to democratize data assets.
- Velocity & Continuous Improvement: Create organizational leverage by improving time-to-insight, debugging speed, and deployment velocity, while continuously evaluating new tools and technologies to elevate data capabilities.
What You Bring
Team & People Leadership
- Leadership Experience: 5+ years in data engineering with 3+ years managing data engineering, machine learning, and data science teams with a focus on coaching senior ICs, career development, and building an inclusive, accountable team culture.
- Working Style & Values: An adaptable, self-motivated leader who thrives in fast-paced, ambiguous environments—balancing strategic vision with hands-on technical guidance, humility, empathy, and a passion for the outdoors.
Technical Architecture & Infrastructure
- Platform & Governance: Hands-on experience managing GCP data infrastructure, enforcing data governance, and maintaining production-grade data access patterns, storage, caching, and optimization standards.
- Modern Data Stack: Extensive proficiency in transforming high-volume datasets in columnar SQL warehouses (BigQuery preferred, or Snowflake) using ELT tools (Dataform, dbt) and orchestrators like Apache Airflow.
- Pipeline & Processing: Proven expertise designing complex SQL/Python pipelines using parallelized processing frameworks (Dataflow, Spark, or similar) and core data modeling techniques (dimensional, star schema).
Engineering Practices & AI/ML Ops
- DevOps & SDLC: Deep familiarity with software engineering best practices, including Docker/Kubernetes, CI/CD pipelines, monitoring/observability tools (Datadog, New Relic, etc.), code reviews, and monthly on-call rotation.
- Applied AI/ML: Track record of guiding teams through the full ML lifecycle (MLOps) to support applied use cases like recommendation, ranking, personalization, and classification engines.
Stakeholder Management & Execution
- Cross-Functional Ownership: Skilled at leading across both platform foundations and applied data products, with the business judgment to prioritize competing stakeholder needs.
- End-to-End Delivery: Proven ability to translate complex business requirements into technical specs, collaborating effectively with stakeholders to own projects from inception to completion.
Bonus Points
- Experience working with geospatial data, maps, tiling, graph databases, and/or routing
- Experience working in a multi-cloud environment (GCP + AWS)
- Experience working at a B2C company
- Skilled at managing infrastructure as code (e.g. Terraform)
Perks & Benefits
- Competitive and equitable compensation, including ownership through equity and performance-based bonuses
- Comprehensive health, dental, and vision coverage to support your physical and mental well-being
- Unlimited PTO in addition to company holidays
- Dedicated time once a month to test and improve our product through company-wide no-meeting days
- Fully paid parental leave to birthing and non-birthing parents
- 401k Match & access to financial wellness resources through Origin
- Remote work stipend to help you design a comfortable and productive home office
- Annual learning stipend to invest in your long-term professional growth and skills
- Exclusive discounts on our subscriptions and merchandise for you and your friends & family
- An authentic investment in you as a human being and a professional—we value your identity as much as your output
Nature celebrates you just the way you are and so do we! At AllTrails we’re passionate about nurturing an inclusive workplace that values diversity. It’s no secret that companies that are diverse in background, age, gender identity, race, sexual orientation, physical or mental ability, ethnicity, and perspective are proven to be more successful. We’re focused on creating an environment where everyone can do their best work and thrive.
Offers of employment are contingent upon the successful completion of a background check. AllTrails will consider all qualified applicants, including those with arrest and conviction records, in a manner consistent with all applicable laws, including the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York City Fair Chance Act. AllTrails participates in the E-Verify program for all remote locations.
By submitting my application, I acknowledge and agree to AllTrails' Job Applicant Privacy Notice. All official recruiting communications from AllTrails will come from an name@alltrails.com email address. Please review sender details carefully, and do not engage with anyone asking for payment or sensitive financial information as part of the hiring process.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.
This range represents our good faith estimate for a successful candidate’s starting base salary. Final offers are determined by a blend of factors including specialized skills, experience, and relevant credentials. In addition to base pay, our total rewards package includes an equity stake in the company and a performance-based bonus program.
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Find JobsMid Level Data Science Analyst Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software13
- Retail10
- Consulting & Professional Services9
- Banking & Financial Services5
- E-Commerce & Online Marketplaces5
Mid Level Data Science Analyst Jobs: Frequently Asked Questions
How do I get a mid level data science analyst job?
Position your experience around ownership, not just execution. Highlight projects where you defined the analytical approach, delivered recommendations to stakeholders, or improved a pipeline on your own initiative. Tailor your resume to show measurable impact, demonstrate fluency with SQL, Python, or R alongside visualization tools, and make clear that you can work independently across the full analysis cycle from scoping through delivery.
Which companies hire mid level data science analysts?
Companies hiring mid level data science analysts right now include Capital One, Walmart, and ZS, based on current listings on Migrate Mate as of August 2026. Hiring at this level covers large enterprises with dedicated analytics teams, mid-size technology and financial services firms building out their data functions, and consulting organizations staffing project-based analyst roles.
Are there remote mid level data science analyst jobs?
Yes, remote work is widely available at this level. About 43% of mid level data science analyst openings are remote or hybrid as of August 2026, reflecting how much of the work centers on code, models, and dashboards that travel well outside an office. Fully on-site roles tend to appear most often in regulated industries like healthcare and finance where data access requirements are stricter.
How do I move up to a mid level data science analyst role?
The move from entry level to mid level is built on demonstrated ownership over time. Early career analysts who take on progressively complex projects, develop a specialty in an area like predictive modeling, A/B testing, or business intelligence, and start presenting findings directly to stakeholders position themselves well. Consistently delivering measurable business impact, rather than just completing assigned tasks, is what signals readiness for mid level responsibilities.
Which industries hire the most mid level data science analysts?
Mid Level data science analyst roles concentrate in Technology & Software, Retail, and Consulting & Professional Services, based on current listings on Migrate Mate as of August 2026. These sectors generate large, complex data sets and face competitive pressure to make faster, evidence-based decisions, which sustains strong demand for analysts who can work independently and communicate insights to non-technical stakeholders.