Data Scientist
About The Position
RDA is a digital transformation consultancy helping future-ready enterprises solve complex business challenges through AI, strategy, and customer experience. We’re expanding our data capabilities and seeking a Data Scientist to design and deliver machine learning solutions that drive measurable business impact. In this role, you’ll work closely with clients to explore data, build predictive models, and bring those solutions into production. You’ll operate at the intersection of hands-on development and client collaboration, contributing to both delivery and early-stage solutioning in a consulting environment. Location Remote. We’re interested in candidates based in Eastern or Central Time Zones, as collaboration happens primarily during EST hours.
Requirements
- 3–8+ years of hands-on experience in machine learning (including model selection, training, tuning, evaluation, and deployment in production environments
- Strong Python Expertise with common ML libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow, PyTorch)
- Solid foundation in statistical modeling and predictive analytics, including experience with data wrangling and feature engineering
- Hands-on experience with Microsoft Azure ML Studio and Microsoft Fabric
- Experience building and deploying ML solutions in cloud environments and working across diverse business domains
- Bachelor’s degree in a related field or equivalent practical experience
Nice To Haves
- consulting background
- data visualization experience
- LLM-based or AI agent solution experience
Responsibilities
- Analyze client data to identify trends, correlations, anomalies, and predictive opportunities
- Build, train, evaluate, and deploy machine learning models across a variety of use cases
- Select appropriate statistical and ML approaches, experiment with alternatives, and optimize model performance
- Prepare and process data for modeling, including cleaning, transformation, and feature engineering
- Integrate ML solutions into client systems in partnership with engineering teams
- Monitor models for drift, bias, and accuracy over time and adjust as needed
- Present insights and recommendations to business stakeholders in a clear, compelling way
- Participate in discovery sessions to understand client objectives and data landscapes
- Support sales and pre-sales by helping scope machine learning opportunities
- Collaborate with cross-functional RDA project teams throughout implementation cycles
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
