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Job description

About Sperry:

Sperry Rail is on a mission critical journey to revolutionize the Rail Flaw Detection industry. Through the continuous development of cutting edge diagnostic technologies and AI assisted analysis, we are transforming railway safety worldwide. Our global engineering teams work collaboratively to develop step-change technologies that define Sperry as the unparalleled market leader. For nearly a century we have repeatedly succeeded in modernizing and improving rail diagnostics through our unrelenting pursuit of improvement. Determined is an understatement. We are obsessed with advancing the science and raising the bar on what’s possible with our ever improving suite of product and service offerings. Emboldened through the shared values of honesty, accountability, passion, integrity and teamwork, we are driven by the challenge and bridging concept with fruition. Each technologist entering Sperry has an opportunity to imprint themselves into our brand and further galvanize a culture of innovation and advancement. Allow us to be clear, Thought Leaders are welcome! We are agile, hungry and invite those with similar passion to join us in challenging the status quo and bringing new ideas to market. Fast paced, high-touch with distinct sense of purpose, we offer more than a job, rather an opportunity to be part of a something different.

Position Summary:

As Data Scientist you will work within the broader Digital Transformation team on the design and development of AI solutions within the Non-Destructive Testing field of Rail Flaw Detection Analysis. This role applies advanced statistical and mathematical techniques to extract insights and knowledge from large and complex datasets. Responsibilities will include analyzing data, building predictive models, and providing actionable recommendations to solve complex business problems. This role works cross-functionally within the engineering organization and with Remote Analysis teams to deliver enhancements and confirm development milestones.

Core Responsibilities:

Data Exploration and Analysis:

• Identify and collect relevant data from various sources, ensuring data quality and integrity.
• Clean, preprocess, and transform raw data to prepare it for analysis.
• Perform exploratory data analysis (EDA) to understand patterns, trends, and relationships within the data.
• Apply statistical techniques and data visualization methods to derive meaningful insights and communicate findings effectively.

Predictive Modeling and Machine Learning:

• Develop and implement predictive models using machine learning algorithms, such as neural networks, classification, clustering, and time series analysis.
• Evaluate and validate model performance using appropriate evaluation metrics and cross-validation techniques.
• Identify feature engineering strategies and perform feature selection to improve model accuracy and interpretability.
• Collaborate with software engineers to deploy models into production systems.

Data Mining and Pattern Recognition:

• Apply data mining techniques to discover patterns, correlations, and trends in complex datasets.
• Use advanced statistical and machine learning methods, such as anomaly detection and association rule mining, to identify hidden patterns and insights.
• Experimentation and Hypothesis Testing:
• Design and conduct experiments to test hypotheses and evaluate the impact of interventions or changes.
• Apply statistical inference and hypothesis testing techniques to draw conclusions and make data-driven recommendations.
• Collaborate with stakeholders to define experimental design, sample sizes, control groups.

Data Visualization and Reporting:

• Create visually compelling and interactive data visualizations to communicate complex findings to non-technical stakeholders.
• Develop dashboards and reports to track key performance indicators (KPIs) and provide regular updates on data-driven insights.

Collaboration and Cross-functional Partnership:

• Collaborate with cross-functional teams, including business analysts, data engineers, and domain experts, to understand business needs and translate them into analytical solutions.
• Communicate effectively with stakeholders to gather requirements, present findings, and provide insights that drive decision-making.

Qualifications – Must Haves:

• Advanced degree (Master’s or Ph.D.) in Data Science, Computer Science, Statistics, Mathematics, or AI related field.
• 4-7 years’ experience within a dedicated Data Scientist role.
• Depth of Statistical Knowledge: Probability, Hypothesis Testing, Regression Analysis, Time Series Analysis.
• Depth of Knowledge with Python programming, Data Visualization (Matplotlib) and Data Structuring (Indexing and Sorting).
• Demonstrative experience with Neutral Networks and Cluster Algorithms.
• Deep Learning Experience: Keras, TensorFlow, PyTorch, Image Recognition.

Qualifications – Desirable:

• Familiarity with Data Prep / Cleaning: Transforming and Cleaning (raw data)
• Experience with AWS-S3

Why Sperry:

• Competitive Salary & Incentive Plan participation.
• Healthcare Benefits
• Generous paid time off and hybrid working flexibility.
• Truly meaningful and engaging work, compelling and intrinsically motivating.
• Immediate contribution to advanced technology development which will have industry changing impact.
• Collaboration across high performing engineering teams with interdependent, well defined achievement goals.
• Opportunity for thought leadership within a highly supportive working environment.

No applicant shall receive less favourable treatment directly or indirectly on the grounds of, Age, Disability, Gender Reassignment, Race, Religion or Belief, Sex, Sexual Orientation, Marriage or Civil Partnership nor Pregnancy or Maternity. Sperry strives to create a welcoming and collaborative environment where all our employees can bring their authentic selves. We show respect and care towards one another and work together to create a safe and collaborative environment where all thoughts and opinions are welcome. The selection of new employees will be based on job requirements and the individual’s suitability and ability to do the job and information sought from candidates will relate only to the qualifications for or requirements of the job.

Job Types: Full-time, Permanent

Pay: £55,000.00-£65,000.00 per year

Benefits:

• Life insurance
• Private medical insurance
• Sick pay
• Work from home

Schedule:

• Day shift
• Monday to Friday

Supplemental pay types:

• Performance bonus

Application question(s):

• How many years experience do you have in a dedicated data scientist role?

Education:

• Master's (required)

Work authorisation:

• United Kingdom (required)

Work Location: In person

Expected start date: 03/07/2023

About Sperry Rail Service

CEO: Jamie O Rourke
Revenue: Unknown / Non-Applicable
Size: 201 to 500 Employees
Type: Company - Private
Website: www.sperryrail.com
Year Founded: 1928