Senior Data Scientist – MMM ID71005

AgileEngine, LLC.

Centrosur

Presencial

COP 72.000.000 - 120.000.000

Jornada completa

Hace 12 días
Generador de candidaturas

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Ventajas ofrecidas por este puesto de trabajo

Growth without limits
Competitive compensation
Flexibility (remote)
Meaningful, modern projects
Collaborative culture
Well-being & support

Descripción de la vacante

AgileEngine seeks a Senior Data Scientist to drive rigorous statistical execution, multi-goal tuning, and algorithmic validation of Meridian MMM frameworks, translating noisy marketing signals and low-resolution data matrices into trusted, multi-objective spend recommendations.

You will formulate heuristic baseline models, ingest structured data from upstream pipelines for client-isolated experimentation, and apply Python with advanced SQL against AWS Athena and PostgreSQL environments.

Formación

  • 5–7 years of professional data science experience, emphasizing time-series analysis, prior distributions, or high-complexity attribution modeling
  • Clear, verifiable experience applying or testing the Meridian MMM framework on real-world datasets.
  • Strong backend proficiency using Python, specifically leveraging tools that reinforce static type systems and structured schemas.
  • Absolute comfort operating entirely inside standard Mac/Linux terminal infrastructure using Bash, shell utilities, and text-based tools
  • Proficiency writing advanced queries to extract and prepare data housed in cloud systems such as AWS Athena or PostgreSQL environments
  • Strong communication skills, specifically the assertiveness to defend a technical or mathematical methodology against a project shortcut that threatens calculation validity

Responsabilidades

  • Expand framework configurations to natively factor in multi-layered client objectives, such as separating mid-funnel brand awareness metrics from immediate revenue generation targets.
  • Formulate robust heuristic models and pragmatic backup strategies to generate valid analytical insights when working with limited or high-variance customer datasets.
  • Safely ingest highly structured fields derived from upstream single source of truth data pipelines to execute client-isolated experimentation.
  • Leverage modern AI-assisted IDE tools to expedite data transformations while applying strict analytical validation to catch tool errors or structural flaws before deployment.
  • Collaborate daily with internal engineering cross-functions via Slack and Google Meet to rapidly resolve ambiguous pipeline requirements or technical dependencies.

Conocimientos

Python
Time-series analysis
Meridian MMM framework
Backend
Mac/Linux terminal
SQL
AWS Athena
PostgreSQL
Communication

Herramientas

Docker
Kubernetes

Descripción del empleo

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Senior Data Scientist to drive rigorous statistical execution, multi-goal tuning, and algorithmic validation of client-specific Meridian MMM frameworks, translating noisy marketing signals and low-resolution data matrices into trusted, multi-objective spend recommendations. You will formulate heuristic baseline models for high-variance datasets, ingest structured data from upstream pipelines for client-isolated experimentation, and apply Python with advanced SQL against AWS Athena and PostgreSQL environments.

WHAT YOU WILL DO
  • Expand framework configurations to natively factor in multi-layered client objectives, such as separating mid-funnel brand awareness metrics from immediate revenue generation targets.
  • Formulate robust heuristic models and pragmatic backup strategies to generate valid analytical insights when working with limited or high-variance customer datasets.
  • Safely ingest highly structured fields derived from upstream single source of truth data pipelines to execute client-isolated experimentation.
  • Leverage modern AI-assisted IDE tools to expedite data transformations while applying strict analytical validation to catch tool errors or structural flaws before deployment.
  • Collaborate daily with internal engineering cross-functions via Slack and Google Meet to rapidly resolve ambiguous pipeline requirements or technical dependencies.
MUST HAVES
  • 5–7 years of professional data science experience, emphasizing time-series analysis, prior distributions, or high-complexity attribution modeling
  • Clear, verifiable experience applying or testing the Meridian MMM framework on real-world datasets.
  • Strong backend proficiency using Python, specifically leveraging tools that reinforce static type systems and structured schemas.
  • Absolute comfort operating entirely inside standard Mac/Linux terminal infrastructure using Bash, shell utilities, and text-based tools
  • Proficiency writing advanced queries to extract and prepare data housed in cloud systems such as AWS Athena or PostgreSQL environments
  • Strong communication skills, specifically the assertiveness to defend a technical or mathematical methodology against a project shortcut that threatens calculation validity.
NICE TO HAVES
  • Familiarity with containerized applications managed under Docker or basic Kubernetes infrastructure paradigms.
  • Practical knowledge of structural time-series models, Bayesian inference techniques, or custom Markov Chain Monte Carlo (MCMC) configurations.
  • Prior experience dealing with multi-account privacy boundaries and strict compliance mandates regarding client data partitioning.
  • Background in analyzing digital platform performance APIs, such as Google Ads, Amazon Advertising, or YouTube Data systems.
PERKS AND BENEFITS
  • Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
  • Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
  • Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
  • Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
  • Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
  • Well-being & support: access local well-being programs and people-focused support tailored to your location
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