Hire machine learning engineers | machine learning engineer remote
Senior Data Scientist / Applied Machine Learning Engineer (Remote)
Location: Remote
Experience: 8+ Years
Type: Contract / Full-Time (based on client needs)
Job Overview
We want a Hire machine learning engineers / Applied Machine Learning Engineer who has vast experience in predictive modeling, causal inference, and advanced analytics to join our team. The expert will play a leading role in enabling decisions across products and business initiatives with support from subject matter experts. This is a fully remote position for professionals who thrive at the intersection of machine learning, business strategy, and cloud data platforms Hire machine learning engineers
Hire machine learning engineers The ideal candidate would be one who has hands-on experience implementing scalable machine learning solutions in Python, applying causal inference methodologies on real-world observational data, and surfacing insights using the latest analytics platforms (Microsoft Fabric, Azure Machine Learning, Power BI) that can be immediately acted upon.
Work with engineering, analytics, and business stakeholders to assess the effects that product features, platform initiatives, and customer programs have on adoption, performance, or revenue outcomes
Duties
As a Hire machine learning engineers / Applied Machine Learning Engineer:
Machine Learning Model Development
Define, Build Train Validate Optimize predictive machine learning models in Python and using modern ML frameworks.
– Use supervised and unsupervised learning methods to solve complex business and product problems.
– Model robustness, scalability, and explainability.
Causal Inference & Impact Analysis
– Perform causal inference and causal impact analysis using observational (non-experimental) data.
– Apply propensity score matching, regression analysis, difference-in-differences, and synthetic control models.
– Assess the effectiveness of initiatives such as telemetry programs, feature rollouts, and adoption strategies.
Product & Telemetry Analytics
– Telemetry data, usage patterns, and product health indicators in evaluating the engagements of customers with features.
– Translation into clear business insights of complicated analytical results for strategic decision making.
– Emerging trends, risks, and opportunities across the customer journey and platform usage
Cloud & Data Platform Integration
– Develop scalable, repeatable data science solutions using Microsoft Fabric environments.
– Utilize Microsoft Azure data services for data ingestion, transformation, and analytics workflows.
Apply, watch, and handle models with Azure Machine Learning steps and MLOps top ways.
Write & Show
Work with Power BI and data teams to put machine learning results into views and main reports. Allow self-check data by adding guesswork and reason insights into report fixes
Teamwork & Talk with Others Involved
Work across functions with building, product, money, and lead groups. Share tech finds and tips clearly to both techy and non-techy crowds.
– Facilitate data-driven decision making at the strategic level and at the operational level.
Requirements
– 8 yrs+ exp in Data Science, Applied ML, or Adv Analytics.
– Highly skilled with python and ml libs e.g. scikit-learn, tensor flow, pytorch.
– Practical knowledge of ms fabric, azure ml, and azure data svcs.
– Solid background in causal inference methods such as:
– Different matching techniques
– Regression based causal models
– Difference-in-differences
– Synthetic controls
– Experience with telemetry data, product analytics, or platform-level business metrics.
– Analytical, problem-solving, and critical-thinking skills.
– Communication skills and ability to present insights to senior stakeholders.
Preferred / Nice-to-Have Skills Hire machine learning engineers
– Experience in the design and operationalization of MLOps pipelines.
– Knowledge of statistical modeling and experimental design.
– Background in SaaS, cloud platforms, or large-scale data environments.
– Familiarity with customer lifecycle analytics and revenue impact modeling.
Work in Agile, cross-functional engineering teams.
Why Join This Opportunity?
This is a fully remote position enabled by flexible collaboration; you can make an impact on the product strategy, customer success, and revenue outcomes; Modern Data Stack consisting of Microsoft Fabric, Azure ML, and advanced analytics tools; Senior-level ownership that drives the get-to-define problem all the way to production for end-to-end data science solutions Hire machine learning engineers
Machine learning, causal inference, and cloud-native analytics are all areas in which professionals can grow their knowledge and expertise.
This professional delivers more than just accuracy of models; he delivers real business impact. He is keen on working with imperfect real-world data, applying causal reasoning to answer what actually caused this outcome rather than what correlates with it. If you like working with stakeholders, explaining complicated concepts simply, and creating solutions that scale, then you are the right fit
Apply Now>>>>> https://www.linkedin.com/jobs/view/4328954464/?refId=A9%2FD5n%2Fuxws6%2Fup8yrPNAw%3D%3D&trackingId=A9%2FD5n%2Fuxws6%2Fup8yrPNAw%3D%3D
Explore More Jobs>>>>> https://diceusajobportal.com
