Job description

Duration: 6 Months Key Responsibilities • Translate complex business and marketing problems into analytical solutions, models, and actionable insights . • Develop statistical models, evaluation metrics, and data science solutions to support business decision-making. • Partner with business, product, and engineering teams to evaluate product impact and key metrics such as engagement, retention, and churn . • Gather, extract, combine, and analyze data from multiple sources using SQL, Python, R, and related tools . • Drive data preparation, restructuring, formatting, validation, and quality checks to ensure datasets are analysis-ready. • Develop reusable and scalable analytical solutions within the team's development processes. • Provide technical guidance and mentorship on data science and analytical projects. • Build stakeholder trust by translating business requirements into tractable analyses, measurable metrics, and clear recommendations . • Ensure appropriate consideration of data privacy, confidentiality, and security throughout data extraction and analysis. Required Qualifications / Skills • Strong experience in data science, business analytics, marketing analytics, or a related field . • Strong SQL skills with experience extracting, joining, transforming, and validating data. • Hands-on experience with Python and/or R for data analysis and statistical modeling. • Experience developing statistical models, analytical frameworks, or evaluation metrics . • Ability to translate ambiguous business problems into structured analytical approaches . • Experience working with large, complex, or multi-source datasets . • Strong understanding of data quality, validation, and preparation for analysis. • Experience collaborating with cross-functional business, product, and engineering stakeholders . • Strong communication skills with the ability to explain technical findings to non-technical stakeholders . Nice to Have • Experience in marketing analytics, customer analytics, or product analytics . • Experience analyzing engagement, retention, churn, or customer lifecycle metrics . • Experience building reusable, scalable data science or analytics solutions . • Experience with data pipelines and data engineering workflows . • Experience with machine learning or advanced statistical modeling . About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com . US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. AI Statement: By applying, you acknowledge that AI-assisted tools may be used during hiring. #LI-AS140

Requirements

Must-haves

Duration: 6 Months
Translate complex business and marketing problems into analytical solutions, models, and actionable insights .
Develop statistical models, evaluation metrics, and data science solutions to support business decision-making.
Partner with business, product, and engineering teams to evaluate product impact and key metrics such as engagement, retention, and churn .
Gather, extract, combine, and analyze data from multiple sources using SQL, Python, R, and related tools .
Drive data preparation, restructuring, formatting, validation, and quality checks to ensure datasets are analysis-ready.
Develop reusable and scalable analytical solutions within the team's development processes.
Provide technical guidance and mentorship on data science and analytical projects.
Build stakeholder trust by translating business requirements into tractable analyses, measurable metrics, and clear recommendations .
Ensure appropriate consideration of data privacy, confidentiality, and security throughout data extraction and analysis.
Required Qualifications / Skills
Strong experience in data science, business analytics, marketing analytics, or a related field .
Strong SQL skills with experience extracting, joining, transforming, and validating data.
Hands-on experience with Python and/or R for data analysis and statistical modeling.
Experience developing statistical models, analytical frameworks, or evaluation metrics .
Ability to translate ambiguous business problems into structured analytical approaches .
Experience working with large, complex, or multi-source datasets .
Strong understanding of data quality, validation, and preparation for analysis.
Experience collaborating with cross-functional business, product, and engineering stakeholders .

Nice-to-haves

Experience in marketing analytics, customer analytics, or product analytics .
Experience analyzing engagement, retention, churn, or customer lifecycle metrics .
Experience building reusable, scalable data science or analytics solutions .
Experience with data pipelines and data engineering workflows .
Experience with machine learning or advanced statistical modeling .

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlpythonmachine learningai

Platform: jobdiva
Effort: medium