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Hybrid Data Scientist /ML Engineer
Crossfire Consulting
- United States
- United States
Über
Position: Data Scientist/ML Engineer Contract Length:
12 months Location:
New York, NY Work Setup:
Hybrid
Our client is a data-driven organization leveraging advanced analytics, machine learning, and cloud technologies to deliver impactful business insights. The
Data Scientist/ML Engineer
will design, build, and deploy scalable machine learning solutions while collaborating with cross-functional teams in a modern enterprise environment.
Data Scientist/ML Engineer Responsibilities
Design, develop, and optimize machine learning models for forecasting, classification, and clustering. Apply advanced analytics, data mining, and statistical techniques to uncover trends and predictive insights. Perform feature engineering, model validation, performance tuning, and deployment using MLOps best practices. Prepare and analyze structured and unstructured data for advanced analytics and machine learning use cases. Develop and maintain Python and PySpark code for data cleansing, enrichment, and validation. Collaborate closely with Data Engineering teams to support and optimize scalable data pipelines. Build, maintain, and troubleshoot
Power BI dashboards , including root-cause analysis of data and visualization issues. Conduct deep-dive analyses and clearly communicate findings to technical and non-technical stakeholders. Partner with architects, engineers, and analysts to define analytical requirements and promote data governance standards. Data Scientist /ML Engineer Qualifications
Required (Must Have):
Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related field. 7+ years of experience
in data science and machine learning engineering roles. Strong hands-on experience with
machine learning algorithms , predictive modeling, and data mining. Advanced proficiency in
Python (required) , including full-stack Python development. Advanced SQL (required)
with strong experience in relational databases. Proficiency in
PySpark (required)
for large-scale data processing and analytics. Azure Databricks Data Engineer Associate certification (REQUIRED). Hands-on experience using
Azure Databricks
in enterprise data and ML environments. Experience with
Generative AI , large language models, and
Natural Language Processing (NLP) . Strong experience with
Machine Learning Operations (MLOps) , including model deployment, monitoring, and lifecycle management. Minimum
3 years of experience with Power BI , DAX queries, and data visualization best practices. Experience with modern data science libraries such as
scikit-learn, pandas, and NumPy . Knowledge of
A/B testing , statistical modeling, and experimental design. Ability to interpret complex datasets and translate insights into actionable business recommendations. Excellent communication, analytical, and problem-solving skills. Nice to Have:
Experience with
Google Cloud Platform (GCP) , including
BigQuery . Exposure to multi-cloud or hybrid cloud data environments. Experience with Oracle or other enterprise database platforms.
This
Data Scientist /ML Engineer
role offers the opportunity to work on high-impact analytics and machine learning initiatives in a collaborative, hybrid environment based in New York, NY. We look forward to reviewing your application! #tech #NoLinkedIn
Sprachkenntnisse
- English
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