Data Scientist

Traackr, Inc.; Mexico; On-site; PHP 4,626,773 - 5,243,676; Full time

Benefits offered by this job

Remote work options

Home office stipend

Coworking subscription

Health insurance

Dental & life insurance

Generous vacation policy

Parental leave

Career development

Job summary

Traackr, Inc. is a remote‑first global SaaS company providing a data‑driven influencer marketing platform. This role focuses on leading ML/AI features, experimentation, and end‑to‑end model lifecycle in production.

You will partner with product and engineering to define success metrics and deliver high‑impact capabilities. The position emphasizes rigorous evaluation, collaboration across teams, and mentorship for engineers to ship with quality and cost efficiency.

Qualifications

• 3+ years delivering data science work that shipped to production or materially influenced product direction.
• Experience collaborating cross‑functionally and communicating clearly with diverse stakeholders; ability to influence without authority.
• Strong Python and SQL skills, with the ability to write maintainable, production‑quality code (testing, reviews, documentation).
• Demonstrated mentorship/enablement—helping other engineers and teams adopt best practices and ship faster with higher quality.

Responsibilities

• Partner with Product and Engineering to identify high‑impact opportunities, frame ambiguous problems, define success metrics, and choose pragmatic approaches (heuristics, statistics, ML, or GenAI).
• Lead rigorous experimentation across teams: hypothesis design, metric/guardrail definition, power analysis, A/B testing (or quasi‑experiments), and clear readouts that drive decisions.
• Build and iterate on ML/AI capabilities that ship to production (e.g., classification, information extraction, ranking/recommendations, and GenAI components such as RAG or developing the agent harnesses for our core agentic journeys), optimizing for value‑added, latency, and cost.
• Establish best‑in‑class evaluation practices for both ML and LLM features: golden datasets, offline/online evaluation plans, regression suites, and monitoring that catches quality drift early.
• Enable engineers to build safely and effectively with AI by coaching on prompt patterns, tool/function calling, structured outputs, guardrails, and debugging/evaluation workflows.

Skills

Data science in production

Cross-functional communication

Python & SQL

Job description

Traackr is a global SaaS technology company providing a data‑driven influencer marketing platform that marketers use to optimize investments, streamline campaigns, and scale programs. Our customers range from some of the world’s largest companies in the beauty and personal care space to digitally native indie brands, which have all made influencer management and engagement a critical practice of their marketing and advertising programs. We are a remote‑first company, and for the folks that like to meet in person, we have offices in San Francisco, New York, Boston, Paris, and London. We operate on a culture of mutual respect, with core value pillars including: Trust, Diversity, Value, Ownership, and Mutual success. This position is 100% remote, with the understanding that occasional in‑person attendance may be required for trainings, meetings, and team gatherings, as determined by your manager.

Responsibilities

• Partner with Product and Engineering to identify high‑impact opportunities, frame ambiguous problems, define success metrics, and choose pragmatic approaches (heuristics, statistics, ML, or GenAI).
• Lead rigorous experimentation across teams: hypothesis design, metric/guardrail definition, power analysis, A/B testing (or quasi‑experiments), and clear readouts that drive decisions.
• Build and iterate on ML/AI capabilities that ship to production (e.g., classification, information extraction, ranking/recommendations, and GenAI components such as RAG or developing the agent harnesses for our core agentic journeys), optimizing for value‑added, latency, and cost.
• Establish best‑in‑class evaluation practices for both ML and LLM features: golden datasets, offline/online evaluation plans, regression suites, and monitoring that catches quality drift early.
• Enable engineers to build safely and effectively with AI by coaching on prompt patterns, tool/function calling, structured outputs, guardrails, and debugging/evaluation workflows.
• Design and support agentic workflows where they add real product value, with clear constraints, observability, and fallbacks.
• Support the end‑to‑end lifecycle of deployed models and AI systems: data requirements, training/fine‑tuning where relevant, validation, deployment, monitoring, incident response, and continuous improvement.
• Raise org‑wide leverage by creating reusable assets (evaluation harnesses, shared datasets, templates, documentation) and running enablement workshops.
• Communicate insights and tradeoffs clearly to technical and non‑technical stakeholders, turning analyses into decisions and measurable impact.
• Champion responsible, privacy‑aware AI: appropriate data handling, bias/fairness considerations where applicable, and human‑in‑the‑loop workflows when needed.

Core Qualifications

• 3+ years (or equivalent) delivering data science work that shipped to production and/or materially influenced product direction.
• Experience collaborating cross‑functionally and communicating clearly with diverse stakeholders; ability to influence without authority.
• Strong Python and SQL skills, with the ability to write maintainable, production‑quality code (testing, reviews, documentation).
• Demonstrated mentorship/enablement—helping other engineers and teams adopt best practices and ship faster with higher quality.

At least 3 of the following

• Strong applied statistics and experimentation skills (A/B testing, causal thinking, metric design, interpretation under uncertainty).
• Proven ability to evaluate and improve models in real conditions: dataset design, error analysis, offline metrics, online measurement, monitoring, and iteration.
• Hands‑on experience building with LLMs in product contexts, including some of: RAG/grounding, tool/function calling, structured outputs, prompt iteration, quality/cost/latency tradeoffs.
• Practical approach to LLM evaluation: golden sets, regression testing, human review loops, and monitoring for quality drift.
• Experience with modern MLOps/LLMOps practices (experiment tracking, ETL pipelines, versioning, CI/CD for ML, observability).
• NLP and information extraction/classification on noisy social/content data.
• Experience developing and evaluating large scale Retrieval, Recommendation‑and‑Search Systems.

Strong plus (optional)

• Experience with large scale data and analytics platforms.
• Experience with Spark or other distributed computing.
• Experience with data lake technologies such as Databricks or equivalent.
• Experience with cloud providers such as AWS or equivalent.

Compensation

$75,000 - $85,000 a year

Benefits

• Competitive Salary.
• Remote Work Options with Hybrid Flexibility and Home Office Set‑Up Stipend.
• Coworking Office Subscription for Collaborative Spaces.
• Health, Dental, and Life Insurance Coverage.
• Open Vacation Policy and Flexible Holiday Schedule to Suit Your Needs.
• Paid Parental Leave to Support Quality Time with Your Loved Ones.
• Career Development, including Internal and External Training Opportunities.

Equal Employment Opportunity

Traackr is an Equal Employment Opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other legally protected characteristics. All your information will be kept confidential in accordance with EEO guidelines.

Unsolicited Resumes

Traackr does not accept unsolicited resumes/CVs from headhunters or recruiting agencies sent directly to Traackr employees or through our website. Traackr will not pay any fees to any third‑party agency or company unless there is a signed agreement with Traackr.

Privacy

Traackr, Inc. has published a Privacy Notice, including CCAP for California and GDPR policies for its UK and European Union subsidiaries, accessible at https://www.traackr.com/privacy-policy.

Questions About Data Processing

All questions, comments, and requests regarding data processing at Traackr should be addressed to [e-mail].