Job Title: Data ScientistJob Description
This senior Data Scientist role (10 to 15 years of experience) plays a pivotal part in driving data-informed decision-making by leveraging advanced analytics, machine learning, and statistical modeling. The position combines deep technical expertise with strategic leadership to design, build, and operationalize robust data science solutions that support critical business and operational use cases. You will lead end-to-end model development and deployment, guide data science best practices, mentor junior team members, and help shape the long-term data strategy and data-driven culture within the organization.
Responsibilities
Expertly handle complex and large-scale datasets, performing in-depth data analysis to derive actionable insights using advanced statistical and machine learning techniques.
Develop, test, and maintain sophisticated machine learning, statistical, and time-series models for use cases such as anomaly detection, predictive maintenance, and operational reliability analysis.
Apply rigorous validation techniques to ensure models are explainable, reliable, and appropriate for operational decision support, including robust statistical validation of key business decisions.
Monitor model performance over time, diagnose model drift, and support controlled updates as data, systems, and operational conditions evolve.
Design and implement end-to-end analytics workflows in a cloud-based Lakehouse environment using Azure Databricks and scalable Spark-based processing for large and complex operational datasets.
Build and maintain data pipelines and feature datasets aligned with enterprise medallion architecture standards to support consistent, reliable, and reusable analytics assets.
Lead feature engineering efforts to identify, create, and select critical data features that enhance the predictive power and stability of machine learning models.
Develop and optimize machine learning algorithms, including deep learning, ensemble methods, and neural networks, to solve complex business and operational problems.
Oversee the deployment of machine learning models into production environments to support real-time or near-real-time decision-making and business applications.
Design and analyze controlled experiments and A/B tests to measure the impact of changes, optimizations, and improvements on key performance indicators.
Create compelling data visualizations and dashboards using tools such as Tableau, Power BI, or custom Python visualizations to clearly communicate complex findings to diverse stakeholders.
Collaborate with IT and data engineering teams to integrate and access data from various sources, data lakes, and data warehouses, ensuring high data quality and consistency.
Design analytics solutions that adhere to data governance, access control, auditability, and data handling standards, ensuring all analytical outputs are traceable to approved inputs.
Operate within platform security constraints to limit uncontrolled data ingress, egress, and access, maintaining compliance with enterprise and regulatory expectations.
Support the implementation of approved AI-enabled analytics and search capabilities, including retrieval-based techniques, ensuring solutions remain verifiable, transparent, and compliant.
Ensure ethical data practices and adherence to data ethics, privacy, and compliance requirements across all data science initiatives.
Partner with engineers, IT leaders, platform teams, business analysts, domain experts, and executives to translate operational and business questions into well-defined analytical approaches.
Participate in technical design and architecture discussions, contributing data science and analytics perspectives to broader technology and platform decisions.
Produce clear, comprehensive technical documentation covering models, data pipelines, assumptions, limitations, and operational procedures to support long-term maintenance and support.
Provide mentorship and guidance to junior data scientists and analysts, fostering their technical growth and professional development.
Act as a strategic leader in promoting a data-driven culture, defining the data science roadmap, and contributing to the organization's long-term data and analytics strategy.
Stay current with the latest data science tools, techniques, frameworks, and industry trends, and evaluate new technologies to continuously improve data science practices.
Essential Skills
10 to 15 years of experience in data science, including a strong track record of implementing data solutions and driving data-driven decision-making.
Master's degree in Data Science, Computer Science, Engineering, Physics, Statistics, Mathematics, or a related quantitative discipline preferred.
Strong proficiency in Python for data analysis, statistical modeling, and machine learning model development.
Proficiency in programming languages and tools commonly used in data science such as Python, R, or Julia.
Solid experience with SQL and working with large-scale structured datasets, including querying, transforming, and manipulating data.
Expert knowledge of machine learning algorithms and their applications, including deep learning, ensemble methods, and neural networks.
Strong foundation in statistical modeling and time-series analysis for forecasting, anomaly detection, and reliability analysis.
Extensive experience with big data technologies and distributed computing frameworks such as Hadoop and Spark.
Demonstrated experience building analytics or machine learning solutions in a production cloud environment, including model deployment and monitoring.
Exceptional skills in data visualization using tools such as Tableau, Power BI, or Python visualization libraries like Matplotlib and Seaborn.
Profound understanding of databases, data manipulation, and data integration across data lakes and data warehouses.
Expertise in data ethics, privacy, and compliance considerations, including designing solutions that meet governance and regulatory requirements.
Outstanding problem-solving and critical thinking abilities, with the capacity to design robust analytical approaches to complex problems.
Strong leadership and communication skills, with the ability to clearly explain analytical methods, assumptions, limitations, and findings to both technical and non-technical stakeholders.
Ability to design analytics solutions that comply with data governance, access control, and auditability requirements and operate within platform security constraints.
Ability to collaborate effectively with cross-functional teams, including engineers, IT, platform teams, and business stakeholders, to align data science initiatives with organizational goals.
Additional Skills & Qualifications
Master's degree or Ph.D. in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Engineering, or Physics is preferred.
Experience supporting analytics in energy, utilities, nuclear, or other highly regulated industries.
Familiarity with industrial or operational time-series data and related analytics use cases.
Experience contributing to MLOps practices, including repeatable training, deployment workflows, model lifecycle management, and experiment tracking.
Understanding of enterprise data governance, access control concepts, and auditability requirements.
Experience with Azure Databricks Lakehouse or similar cloud-based analytics platforms and medallion architecture concepts.
Ability to design and analyze A/B tests and other experimental frameworks to evaluate changes and improvements.
Experience implementing AI-enabled analytics and search capabilities, including retrieval-based techniques, in a governed enterprise environment.
Demonstrated ability to mentor and coach junior data scientists and analytics professionals.
Strong documentation skills, with the ability to create clear, maintainable technical documentation for models, pipelines, and analytics workflows.
Work Environment
This role operates in an onsite work environment, providing close collaboration with engineers, IT leaders, platform teams, and other stakeholders. You will work within a modern cloud-based analytics ecosystem, including an Azure Databricks Lakehouse environment and scalable Spark-based processing for large and complex operational datasets. The position involves working with structured and time-series data from operational systems, often within a highly governed and regulated @context that emphasizes data security, access control, and auditability. You will follow established enterprise standards for data governance, model lifecycle management, and experiment tracking, and you will operate within defined platform security constraints that control data ingress, egress, and access. The environment supports cross-functional collaboration, technical design discussions, and ongoing innovation in advanced analytics and applied AI.
Job Type & Location
This is a Contract position based out of Birmingham, AL.
Pay and Benefits
The pay range for this position is $55.00 - $65.00/hr.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following: - Medical, dental & vision - Critical Illness, Accident, and Hospital - 401(k) Retirement Plan - Pre-tax and Roth post-tax contributions available - Life Insurance (Voluntary Life & AD&D for the employee and dependents) - Short and long-term disability - Health Spending Account (HSA) - Transportation benefits - Employee Assistance Program - Time Off/Leave (PTO, Vacation or Sick Leave)
Workplace Type
This is a fully onsite position in Birmingham,AL.
Application Deadline
This position is anticipated to close on May 13, 2026.
About Actalent
Actalent is a global leader in engineering and sciences services and talent solutions. We help visionary companies advance their engineering and science initiatives through access to specialized experts who drive scale, innovation and speed to market. With a network of almost 30,000 consultants and more than 4,500 clients across the U.S., Canada, Asia and Europe, Actalent serves many of the Fortune 500.
The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
If you would like to request a reasonable accommodation, such as the modification or adjustment of the job application process or interviewing process due to a disability, please email actalentaccommodation@actalentservices.com for other accommodation options.
San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records.
Massachusetts Lie Detector: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.
