Data Analytics Manager
Client : PREMIER HOME HEALTH CARE SERVICES, INC.
The role of the Senior Data Analytics Manager is to work closely with leaders across the company
to support and implement high quality, data-driven decisions. They will ensure data accuracy and
consistent reporting by designing and creating optimal processes and procedures using advanced
data modeling, predictive modeling and analytical techniques to interpret key findings from
company data and leverage these insights into initiatives that will support business outcomes.
Qualifications:
1. Educational: Minimum of a BSc/BA in Computer Science, Statistics, Data Management or
a related field.
2. Travel: Travel may be required for business purposes. If so, the employee must have a
valid driver s license issued by the state in which they work and a satisfactory driving
record.
Work Experience:
a. At least 10 15 years of experience in a position monitoring, managing, manipulating
and drawing insights from data.
b. A minimum of two years within the healthcare industry.
c. Experience and proficiency with the following tools/programs:
1. Programming skills with querying languages SQL, Python, R, SAS, etc.
2. Big data tools: Teradata, Aster, Hadoop, etc.
3. Testing tools such as Adobe Test & Target.
4. Data visualization tools: Tableau, Power BI, Qlik, Raw, chart.js, etc.
5. ETL tools: SSIS, Blendo, or Stitch.
6. Adobe Analytics and other analytics tools.
7. Microsoft Office Suite: Word, Excel, Outlook, Visio, PowerPoint
8. Working knowledge of data mining principles: predictive analytics, mapping,
collecting data from multiple data systems on premises and cloud-based data
sources.
9. Strong experience with data analysis techniques: Regression analysis, Monte Carlo
simulation, Factor analysis and Time series analysis.
d. Understanding of and experience using analytical concepts and statistical techniques:
hypothesis development, designing tests/experiments, analyzing data, drawing
conclusions, and developing actionable recommendations for business units.
e. Ability to translate business problems into analytical frameworks and models.
f. Experience and knowledge of statistical modeling techniques: GLM multiple regression,
logistic regression, log-linear regression, variable selection, etc.
Client : PREMIER HOME HEALTH CARE SERVICES, INC.
The role of the Senior Data Analytics Manager is to work closely with leaders across the company
to support and implement high quality, data-driven decisions. They will ensure data accuracy and
consistent reporting by designing and creating optimal processes and procedures using advanced
data modeling, predictive modeling and analytical techniques to interpret key findings from
company data and leverage these insights into initiatives that will support business outcomes.
Qualifications:
1. Educational: Minimum of a BSc/BA in Computer Science, Statistics, Data Management or
a related field.
2. Travel: Travel may be required for business purposes. If so, the employee must have a
valid driver s license issued by the state in which they work and a satisfactory driving
record.
Work Experience:
a. At least 10 15 years of experience in a position monitoring, managing, manipulating
and drawing insights from data.
b. A minimum of two years within the healthcare industry.
c. Experience and proficiency with the following tools/programs:
1. Programming skills with querying languages SQL, Python, R, SAS, etc.
2. Big data tools: Teradata, Aster, Hadoop, etc.
3. Testing tools such as Adobe Test & Target.
4. Data visualization tools: Tableau, Power BI, Qlik, Raw, chart.js, etc.
5. ETL tools: SSIS, Blendo, or Stitch.
6. Adobe Analytics and other analytics tools.
7. Microsoft Office Suite: Word, Excel, Outlook, Visio, PowerPoint
8. Working knowledge of data mining principles: predictive analytics, mapping,
collecting data from multiple data systems on premises and cloud-based data
sources.
9. Strong experience with data analysis techniques: Regression analysis, Monte Carlo
simulation, Factor analysis and Time series analysis.
d. Understanding of and experience using analytical concepts and statistical techniques:
hypothesis development, designing tests/experiments, analyzing data, drawing
conclusions, and developing actionable recommendations for business units.
e. Ability to translate business problems into analytical frameworks and models.
f. Experience and knowledge of statistical modeling techniques: GLM multiple regression,
logistic regression, log-linear regression, variable selection, etc.