Lead Data Scientist

Murray Resources

Shelton, CT, United States

16 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

7 years minimum

Compensation

$165,000.0 - $175,000.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Geographic Information Systems Statistical Hypothesis Testing Python (Programming Language) Regression Analysis Reliability Engineering SQL Databases Test Data

Job description

Trend the company’s multi-modal test data over time internal flaw detection, induction, and eddy current for defect growth and surface condition degradation across its non-stop inspection programs in North America.
Connect raw test measurements and their metadata to the physical conditions they represent: internal defects, surface conditions, rail flaws.
Analyze defect and error types and frequency by subdivision to identify where risk is concentrated and how it moves.
Apply risk-based models to estimate the probability and consequence of failure.
Own the KPIs for the monthly operational review and customer account review meetings.
Present findings to the commercial team in a form they can use in account conversations.
Work with the analysis organization so that what the data shows about defect and surface-condition patterns reaches the analysts reviewing that track.
Present risk findings to customers alongside the commercial team.
Identify gaps in current data collection and recommend what the company should capture to support better analysis.
Validate findings against field conditions with track engineering and testing teams.
Hire and line manage the two further seats in the pod, and direct their work.
Write and maintain documentation so that the analysis is transferable rather than held tacitly., This is what you will do: This Development Scientist II will be a key team member in Alexion’s External Analytical Development and Quality Control group. This position is respons…
9 days ago +

Requirements

Statistical depth: probability, hypothesis testing, regression analysis, time series analysis
SQL and Python, or equivalent analysis tooling
Risk modelling or reliability engineering
GIS or geospatial data analysis
Experience applying statistical and risk-modelling methods to physical or engineered systems rail, industrial, energy, or a comparable setting
Demonstrable experience managing staff across the full employee lifecycle
A credible and confident communicator, written and verbal, at all levels of a business
Ability to make effective decisions and to keep calm under pressure
High level of honesty and integrity
A collaborative, team-first mindset
Preferred:
Bachelor’s degree in applied mathematics, statistics, physics, engineering, or a related quantitative field; advanced degree welcome
Typically 7+ years analyzing large technical datasets
Linear referencing or corridor-level network data for example pipeline integrity, highway, or utility corridor work
Rail or transportation specifically
Sensing technologies: ultrasonics, induction, eddy current