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About The Company
Ascent has recently been acquired by Acuity Analytics, marking a significant milestone in its growth trajectory. Acuity Analytics is renowned for its strong global reputation, an impressive client portfolio, and ambitious plans for expansion. The company specializes in delivering deep insights and domain-led digital transformation services to high-growth and heavily regulated organizations across various industries. Their core mission is to enhance client performance and operational efficiency through innovative talent, cutting-edge technology, and strategic partnerships. At Acuity Analytics, the focus is on fostering a collaborative environment where data-driven solutions and technological excellence drive meaningful business outcomes.
About The Role
We are seeking an experienced Senior Data Scientist to join our dynamic team. In this role, you will be responsible for designing, building, and optimizing intelligent recommendation and ranking solutions that significantly improve customer outcomes. Working within a collaborative environment alongside data scientists, data engineers, and product teams, you will develop production-ready machine learning models, leverage behavioral analytics, and apply advanced NLP techniques to address complex business challenges. Your expertise will enable the deployment of scalable models using large-scale datasets on platforms such as Databricks and Spark, ensuring continuous performance improvements in live systems. This position offers an exciting opportunity for professionals passionate about solving real-world problems through innovative machine learning solutions that generate measurable business value.
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Qualifications
- Strong commercial experience in Machine Learning and predictive modeling
- Proficiency in behavioral analytics and user behavior modeling
- Hands-on experience with Natural Language Processing (NLP)
- Extensive experience using Databricks and Apache Spark
- Proven track record in building recommendation or ranking systems
- Solid knowledge of statistical modeling and model evaluation techniques
- Experience designing and analyzing product experimentation, including A/B testing frameworks
- Proficiency in Python programming and familiarity with machine learning libraries
- Experience working with large datasets and developing scalable ML solutions
- Strong analytical and problem-solving skills
- Excellent communication skills for conveying technical concepts to diverse stakeholders
- Collaborative mindset with experience in cross-functional Agile teams
- Passion for building production-quality machine learning solutions
- Ability to balance experimentation with delivering tangible business results
Responsibilities
- Design, develop, and deploy machine learning models for recommendation and ranking systems
- Analyze behavioral data to identify patterns and opportunities for system optimization
- Develop NLP solutions to enhance matching and search functionalities
- Build scalable machine learning pipelines utilizing Databricks and Spark platforms
- Design, execute, and assess product experiments to improve model performance and accuracy
- Monitor, tune, and continuously optimize deployed machine learning models for better results
- Collaborate with Data Scientists, Data Engineers, Product Managers, and stakeholders to deliver impactful solutions
- Apply statistical techniques to evaluate model effectiveness and support data-driven decision making
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Benefits
- Competitive salary and comprehensive benefits package
- Opportunities for professional growth and development
- Collaborative and innovative work environment
- Access to cutting-edge tools and technologies
- Flexible working arrangements
- Participation in impactful projects with high-profile clients
Equal Opportunity
We are an equal opportunity employer committed to fostering an inclusive environment. We welcome applications from candidates of all backgrounds and experiences. Diversity and inclusion are integral to our success, and we strive to create a workplace where everyone feels valued, respected, and empowered to contribute to our collective growth.
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