Soni Resources
We are seeking an experienced Senior Data Scientist with a strong foundation in applied machine learning and production-grade AI development. This role provides the opportunity to drive real business impact by designing, building, and deploying advanced data science solutions across multiple product lines and operational functions.
You will join a collaborative team of data scientists, data engineers, and product stakeholders working together to accelerate enterprise innovation through predictive analytics, automation, and intelligent decisioning. Success in this role requires hands-on development skills, analytical rigor, and a passion for turning data into measurable outcomes.
Key Responsibilities
Lead end-to-end development of ML use cases, guiding junior data scientists throughout execution.
Conduct data exploration, sampling, cleansing, and feature engineering to prepare high-quality analytical datasets.
Build and evaluate predictive models using advanced statistical and machine learning techniques to solve complex business problems.
Assess source data quality and implement controls throughout development and production.
Work with engineering and MLOps teams to package and deploy models into enterprise environments.
Introduce new statistical or mathematical methodologies as necessary to enhance model performance.
Partner with stakeholders to identify opportunities for leveraging data to drive actionable insights and operational improvements.
Create clear visualizations and present findings to key decision-makers.
Perform routine data validation and quality checks to ensure reliable and accurate outputs.
Contribute to the standardization of data science practices, tools, and workflows across the organization.
Stay current with industry trends and continuously explore innovative technologies and approaches. You Are
Passionate about modern AI/ML advances and eager to apply them to real-world solutions.
Curious, analytical, and comfortable leading complex data science initiatives.
A team-oriented problem solver who enjoys collaborating with cross-functional partners.
Motivated by seeing your work deployed in production and generating tangible business value. Qualifications
PhD with 2+ years of experience
or
Master's degree with 4+ years in Computer Science, Statistics, Engineering, Applied Mathematics, or a related field.
3+ years of hands-on machine learning development experience.
Deep understanding of data analysis and statistical modeling techniques.
Familiarity with a wide range of ML methods (e.g., clustering, decision trees, boosting, neural networks) and awareness of practical trade-offs.
Experience designing and executing experimental frameworks.
Strong hands-on skills in data wrangling, fuzzy matching, and distributed computing.
Proficiency in Python and related ML libraries.
Solid foundation in algorithms and model optimization.
Excellent communication skills with the ability to influence stakeholders and present to both technical and non-technical audiences.
Proven ability to provide technical guidance and mentorship to peers.
Compensation:
$115,000 to $190,000 annually Salary is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications.
You will join a collaborative team of data scientists, data engineers, and product stakeholders working together to accelerate enterprise innovation through predictive analytics, automation, and intelligent decisioning. Success in this role requires hands-on development skills, analytical rigor, and a passion for turning data into measurable outcomes.
Key Responsibilities
Lead end-to-end development of ML use cases, guiding junior data scientists throughout execution.
Conduct data exploration, sampling, cleansing, and feature engineering to prepare high-quality analytical datasets.
Build and evaluate predictive models using advanced statistical and machine learning techniques to solve complex business problems.
Assess source data quality and implement controls throughout development and production.
Work with engineering and MLOps teams to package and deploy models into enterprise environments.
Introduce new statistical or mathematical methodologies as necessary to enhance model performance.
Partner with stakeholders to identify opportunities for leveraging data to drive actionable insights and operational improvements.
Create clear visualizations and present findings to key decision-makers.
Perform routine data validation and quality checks to ensure reliable and accurate outputs.
Contribute to the standardization of data science practices, tools, and workflows across the organization.
Stay current with industry trends and continuously explore innovative technologies and approaches. You Are
Passionate about modern AI/ML advances and eager to apply them to real-world solutions.
Curious, analytical, and comfortable leading complex data science initiatives.
A team-oriented problem solver who enjoys collaborating with cross-functional partners.
Motivated by seeing your work deployed in production and generating tangible business value. Qualifications
PhD with 2+ years of experience
or
Master's degree with 4+ years in Computer Science, Statistics, Engineering, Applied Mathematics, or a related field.
3+ years of hands-on machine learning development experience.
Deep understanding of data analysis and statistical modeling techniques.
Familiarity with a wide range of ML methods (e.g., clustering, decision trees, boosting, neural networks) and awareness of practical trade-offs.
Experience designing and executing experimental frameworks.
Strong hands-on skills in data wrangling, fuzzy matching, and distributed computing.
Proficiency in Python and related ML libraries.
Solid foundation in algorithms and model optimization.
Excellent communication skills with the ability to influence stakeholders and present to both technical and non-technical audiences.
Proven ability to provide technical guidance and mentorship to peers.
Compensation:
$115,000 to $190,000 annually Salary is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications.