Data Scientist-Advanced Analytics
IBM
**Introduction**
We are seeking a skilled and visionary Data Scientist to join our team, driving data-driven insights and transformative AI/ML solutions. In this role, you will analyze and interpret complex data to uncover valuable patterns, solve intricate business challenges, and create predictive models that deliver measurable impact. Leveraging cutting-edge AI tools, machine learning, and deep learning techniques, you will design, develop, and deploy scalable applications on cloud infrastructure. Beyond technical expertise, you will collaborate closely with clients and cross-functional teams to align AI solutions with strategic business objectives, ensuring that data-driven insights translate into actionable recommendations. If you are passionate about harnessing the power of data to shape innovative solutions and possess strong consulting capabilities, we invite you to join our dynamic and collaborative environment.
**Your role and responsibilities**
Job Description:
As a Senior Data Scientist, you will lead the development of AI/ML models and data-driven strategies to address complex business challenges. You are expected to independently drive the end-to-end lifecycle of analytics projects—from problem definition and data preparation to model deployment and performance optimization. With a strong foundation in machine learning, data engineering, and business acumen, you will play a critical role in transforming insights into actionable business impact.
You will also be a trusted advisor to both internal teams and clients, contributing to solution architecture, project planning, and the mentorship of junior team members.
Responsibilities:
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Lead the design, development, and deployment of advanced machine learning models and AI solutions
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Collaborate with business stakeholders to define project goals, success criteria, and measurable impact
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Apply statistical analysis, data mining, and machine learning techniques to solve real-world business problems
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Guide data engineering processes including data collection, cleansing, transformation, and feature engineering
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Implement and maintain scalable pipelines using MLOps best practices
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Utilize cloud platforms (e.g., AWS, Azure, GCP, or IBM Cloud) for AI/ML solution development and deployment
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Communicate insights, results, and technical concepts to both technical and non-technical audiences
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Mentor junior data scientists and contribute to team knowledge sharing and best practice development
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Stay current with AI/ML advancements and assess applicability to projects or solutions
**Required technical and professional expertise**
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7+ years of experience in data science, machine learning, or advanced analytics roles
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Strong proficiency in Python and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch)
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Experience working with large datasets and data tools (e.g., SQL, Spark, Pandas)
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Familiarity with MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow)
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Hands-on experience deploying models into production environments using cloud services
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Proven ability to work with cross-functional teams and influence decision-making using data
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Excellent problem-solving, critical thinking, and communication skills
**Preferred technical and professional experience**
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Background in finance, retail, manufacturing, or another domain-specific industry
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Experience with real-time data processing or streaming analytics
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Exposure to deep learning, natural language processing, or time-series forecasting
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Certification in cloud-based AI/ML tools is a plus (e.g., AWS Machine Learning Specialty, Azure AI Engineer Associate)
IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
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