Senior Manager
4 weeks ago
Title: Senior Manager, Data Science Company Profile: NPS Prism is a market-leading, cloud-based CX benchmarking and operational improvement platform owned by Bain & Company.
NPS Prism provides its customers with actionable insights and analysis that guide the creation of game-changing customer experiences.
Based on rock-solid sampling, research, and analytic methodology, it lets customers see how they compare to their competitors on overall NPS, and on every step of the customer journey. With NPS Prism you can see where you're strong, where you lag, and how customers feel about doing business with you and your competitors, in their own words.
The result: Prioritize the customer interactions that matter most.
NPS Prism customers use our customer experience benchmarks and insights to propel their growth and outpace the competition. Launched in 2019, NPS Prism has rapidly grown to a team of over 200, serving dozens of clients around the world.
NPS Prism is 100% owned by Bain & Company, one of the top management consulting firms in the world and a company consistently recognized as one of the world's best places to work.
We believe that diversity, inclusion, and collaboration is key to building extraordinary teams.
We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. Position Summary: NPS Prism has experienced tremendous growth as a standalone software and data business over the past few years and is making the leap from being a consulting-led business to a technology-led business.
Given that shift, we are looking to build our team with world-class team members to help drive business growth to its full potential in this next phase.
This is a great opportunity to help build the largest startup owned by Bain & Company and take NPS Prism into the future. Role Overview: We are seeking a hands-on Senior Manager, Data Scientist to lead a talented team of data scientists and analysts, drive advanced analytics projects, and implement machine learning models to solve complex business challenges.
You will play a pivotal role in shaping the data science strategy, managing large-scale data-driven projects, and fostering a culture of collaboration and innovation within the team. This role requires a strong mix of leadership, technical expertise, and strategic thinking.
As a Senior Manager, Data Scientist, you will also act as a thought leader, driving continuous improvement in analytics methodologies and fostering partnerships across the organization. Key Responsibilities: Leadership & Management: Lead and mentor a high-performing team of data scientists, analysts, and data engineers. Set strategic direction for the data science function, aligning with organizational goals. Drive recruitment, team development, and performance management within the data science team. Foster a collaborative, innovative, and results-driven team culture. Project Management: Oversee end-to-end data science projects from conception through implementation, including scoping, resource management, and delivery. Work cross-functionally with engineering, product, and business teams to identify data science use cases that solve key business problems. Ensure project timelines and deliverables are met with high quality. Technical Expertise: Design, develop, and deploy predictive models, machine learning algorithms, and AI-based solutions to drive business insights and automation. Spearhead the development of autonomous AI agents that adapt, learn, and make decisions in dynamic environments, leveraging reinforcement learning, LLMs, and multi-agent systems. Architect and optimize agent-based AI frameworks to enhance automation, decision-making, and operational efficiency, collaborating with engineering teams to integrate cutting-edge AI research into real-world applications. Analyze large, complex data sets using statistical and machine learning techniques. Collaborate with engineering and data teams to ensure the scalability, reliability, and performance of models in production environments. Identify and apply the latest tools, techniques, and best practices in data science and AI. Stakeholder Engagement: Partner with senior leadership, product teams, and key stakeholders to understand business needs and provide actionable insights. Communicate technical concepts and results clearly to both technical and non-technical audiences. Present findings, insights, and recommendations to senior executives and decision-makers. Innovation & Strategy: Drive continuous improvement in analytics methodologies and data science processes. Stay current with industry trends, emerging technologies, and best practices in AI, ML, and data analytics. Lead initiatives to implement new technologies and methodologies that enhance the company's analytics capabilities. Qualifications: Education: Bachelor's degree in computer science, Data Science, Statistics, Mathematics, or a related field.
A Master's degree or PhD is highly preferred. Experience: 12+ years of experience in data science, analytics, or related fields, with at least 5 years in a management or leadership role. Proven experience in building and deploying machine learning models and advanced analytics solutions in production environments. Strong background in programming languages such as Python, R, or Scala. Experience with big data platforms such as Hadoop, Spark, and cloud platforms (AWS, GCP, or Azure). Skills: Strong understanding of machine learning, deep learning, and AI techniques and their application to real-world problems. Excellent analytical and problem-solving skills, with a focus on translating business requirements into technical solutions. Demonstrated leadership skills with the ability to build, manage, and inspire a high-performing team. Exceptional communication skills, with the ability to convey complex ideas to diverse audiences. Ability to work in a fast-paced, dynamic environment with competing priorities. Strong understanding of GenAI concepts and architectures knowledge of using it for different use cases. Good understanding and experience of Uplift models to measure impact of a treatment Experience with multiple data science model techniques to create POCs with different models to measure performance Preferred Qualifications: Bachelors or Master's degree in computer science, Engineering, or a related field. Experience with machine learning models and tools Strong, proven track record solving complex business problems with machine learning within a fast-paced business Formal or informal experience managing and developing a team focused on developing machine learning solutions Strong Understanding and hands-on experience into Text Analytics, NLP, and large language model deployments Experience into concepts of Topic Modelling and Sentiment Analysis will be preferred candidate Experience in solving Text Analytics/NLP/machine learning problems with modern machine learning software stack (Python, Tensorflow, Pytorch, Spark) as well as modern machine learning algorithm stack (Transformers, Graph Neural Networks, boosted decision trees, GenAI, statistical inference) Powered by JazzHR
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