Científico de Datos (Sr) - Especialista en Machine Learning y Cloud MLOpsCABA, Buenos Aires, Argentina ARG HeadquarterAR$ *****,**********,00 (Argentine Peso)Ofertas de empleo Científico de Datos (Sr) - Especialista en Machine Learning y Cloud MLOpsAcerca del puesto Científico de Datos (Sr) - Especialista en Machine Learning y Cloud MLOpsMaxIT Consulting - Max Corporate Group, es una Empresa con sede en Belgrano, CABA y Tampa, Fl, USA que es Líder en el sector y ofrece Servicios de Outsourcing especializados para grandes Compañías a nivel local e internacional.En esta ocasión, nos encontramos en búsqueda de un Data Scientist (Sr) - Especialista en Machine Learning y Cloud MLOps para cubrir una vacante en Buenos Aires.
Nuestro Partner se trata de una empresa de capitales Españoles, con SIGNIFICATIVO reconocimiento y trayectoria a nivel internacional y amplia presencia a los largo del globo con distintos servicios de Tecnología y en continua expansión.
Amplias posibilidades de crecimiento y estabilidad en puesto.Se requieren candidatos de Argentina para trabajar bajo modalidad Relación de Dependencia (RRDD) o Freelance (Contractor).
¡Sumate a esta increíble posibilidad de seguir creciendo y de trabajar con los mejores!
Consideraciones generales:- El trabajo bajo RRDD será vinculo directo coon nuestro Partner español, full-time y a largo plazo.
- La asignación Freelance | Contractor será con MaxIT y se estipula una carga part-time (80hs mensuales) por el término de 4 meses + posibles renovaciones.
- En ambos casos la asignación es 100% Remota desde cualquier parte de Argentina o LATAM.Skills / Requisitos técnicos:1.
Experiencia en Desarrollo de Modelos de Machine Learning / Deep Learning:- Al menos 3 años de experiencia en el desarrollo de modelos de Machine Learning (ML) y Deep Learning (DL).
- Experiencia en la implementación y optimización de modelos para diferentes casos de negocio, desde análisis predictivo hasta reconocimiento de patrones complejos.2.
Conocimiento en Programación y Librerías de ML/DL:- Dominio en programación con Python, utilizando librerías como TensorFlow, Keras, y PyTorch para el desarrollo y entrenamiento de modelos.
- Conocimiento de PySpark y Spark para procesamiento distribuido de datos.Scala: Experiencia en el uso de Scala para tareas de procesamiento de datos, especialmente en el entorno Spark.3.




Experiencia en SQL y Manejo de Bases de Datos:.
Use performance data to continuously improve lists, scripts, workflows, SDR execution, and campaign strategy.
Maintain CRM hygiene, accurate lead stages, follow-up tasks, campaign attribution, and reporting discipline.
Reduce unnecessary manual work through automation while maintaining high data quality and strong SDR execution.
Previous experience in a staffing agency, recruitment firm, RPO, talent acquisition company, HR services business, or workforce solutions company.
Strong hands-on experience building and managing outbound prospecting workflows using Apollo or similar sales intelligence and engagement platforms.
Demonstrated experience creating, enriching, validating, segmenting, and prioritizing outbound prospect lists.
Strong understanding of outbound cold calling, SDR workflows, call prioritization, prospecting sequences, follow-up cadences, and qualified meeting generation.
Experience working directly with SDRs or BDRs and improving their performance through call review, coaching, scripts, objection handling, and process development.
Ability to analyze outbound funnel performance and identify whether problems are caused by targeting, list quality, messaging, call execution, follow-up, or qualification.
Experience building or improving outbound sales systems and processes from the ground up.
Experience creating multichannel outbound campaigns across phone, email, LinkedIn, and CRM-based follow-up.
Strong understanding of staffing and recruitment buyer personas, pain points, objections, and sales motions.
Experience creating outbound messaging, cold-call scripts, email copy, LinkedIn messaging, and objection-handling frameworks.
Experience using AI and automation tools to improve list quality, prospect research, hiring-signal identification, segmentation, personalization, campaign development, and workflow efficiency.




Strong analytical and operational mindset with the ability to translate outbound performance data into practical improvements.
Highly organized, process-driven, and comfortable operating independently in a fast-paced startup environment.
Comfortable joining live sales calls, listening to SDR recordings, reviewing call notes, and providing direct performance feedback.
Comfortable being hands-on with execution rather than operating only at a strategy or management level.
Preferred Qualifications:
Experience with HubSpot, Salesforce, Outreach, Salesloft, LinkedIn Sales Navigator, ZoomInfo, Clay, Instantly, Smartlead, Zapier, Make, or similar GTM tools.
Experience managing or supporting high-volume cold-calling environments.
Familiarity with power dialers, parallel dialing, call analytics, and SDR productivity tools.
Experience developing outbound motions targeting U.S.
-based SMBs and mid-market companies.
Experience building outbound systems in a startup or high-growth environment with limited resources.
Experience improving outbound performance without significantly increasing SDR headcount.
Familiarity with AI-assisted lead research, enrichment, segmentation, call analysis, and messaging workflows.
What success looks like:
Within the first ***** days:
SDRs consistently have enough high-quality, phone-ready prospects to maintain strong daily outbound activity.
Prospecting and list-building workflows are structured, repeatable, and increasingly automated.
Call scripts, objection handling, qualification criteria, and follow-up processes are clearly documented and actively improving.
SDR calls are reviewed regularly and coaching is tied to measurable performance data.
Outbound reporting clearly identifies where conversion is succeeding or breaking down.
Within the first 90 days:
HireHawk has a repeatable and scalable phone-first outbound system.
Manual list-building requirements have been significantly reduced.
SDR productivity and qualified meeting generation have improved.
Clear outbound playbooks and SOPs are in place.
Email and LinkedIn campaigns are being tested and scaled based on their ability to support or independently generate qualified opportunities.
The outbound engine is structured well enough to support additional SDR headcount without creating operational bottlenecks.
#J-*****-Ljbffr

📌 Científico De Datos Senior - Ml, Cloud Mlops & Liderazgo Remoto (La Pampa)
🏢 HireHawk
📍 La Pampa