Data Scientist ML Engineer

Summary: The role of Senior Data Science & AI Specialist requires an experienced professional with 16-18 years of expertise to lead advanced data solutions, AI/ML innovation, and cloud-driven architectures. The position emphasizes proficiency in programming, data handling, visualization, statistics, and machine learning techniques. The candidate must possess mandatory skills in various technologies and frameworks relevant to data science and AI. This role is pivotal in driving the organization's data strategy and innovation initiatives.

Key Responsibilities:

• Lead advanced data solutions and AI/ML innovation.
• Design and implement cloud-driven architectures.
• Handle data wrangling, cleaning, transformation, and feature engineering.
• Create visualizations using tools like Splunk and Power BI.
• Apply statistical methods and machine learning techniques for model training and evaluation.

Key Skills:

• Programming: Python, SQL, Hive, Pig, Scala/Java (big data).
• Data Handling: Wrangling, cleaning, transformation, feature engineering.
• Visualization: Splunk, Power BI dashboards.
• Statistics & Math: Applied statistics, multivariable calculus, linear algebra.
• ML Techniques: Decision Trees, Random Forest, kNN, Naive Bayes, SVM, model training & evaluation.
• Mandatory Skills: Apache Spark, MS SQL Server, PostgreSQL, Cloud Solution Architecture, Industrial AI (Edge & ML), R - Data Science, AR/VR/MR, SQLAlchemy, Performance Engineering.

Salary (Rate): undetermined

City: undetermined

Country: UK

Working Arrangements: undetermined

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Hiring: Senior Data Science & AI Specialist (16-18 years)

We're seeking an experienced professional to lead advanced data solutions, AI/ML innovation, and cloud-driven architectures.

Key Expertise:
. Programming: Python, SQL, Hive, Pig, Scala/Java (big data)
. Data Handling: Wrangling, cleaning, transformation, feature engineering
. Visualization: Splunk, Power BI dashboards
. Statistics & Math: Applied statistics, multivariable calculus, linear algebra
. ML Techniques: Decision Trees, Random Forest, kNN, Naive Bayes, SVM, model training & evaluation
. Mandatory Skills: Apache Spark, MS SQL Server, PostgreSQL, Cloud Solution Architecture, Industrial AI (Edge & ML), R - Data Science, AR/VR/MR, SQLAlchemy, Performance Engineering

Experience: 16-18 years
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