About FiSec Global
Sourced by ZipRecruiter
Industry
It services
Company size
201 - 500 Employees
Headquarters location
Fremont, CA, US
Year founded
2015
Other
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Job description
Job Title: Lead Data Scientist
Location: Chicago IL (Hybrid Model) (3WFO/2WFH)
Duration: Long Term
The Analytics and Insights team is seeking a data scientist who loves working on complex problems and getting things done.
The ideal candidate combines excellent business acumen and communication skills with outstanding analytical skills. If you are detail-oriented, enjoy solving complex data challenges, and are passionate about data, we want to hear from you.
As a Data Scientist, you will work with data analysts, managers and engineers to: resolve ambiguity with data, play a crucial role in the iteration and optimization of analytics and ML products and support data-driven decision-making on a key project for the organization.
You'll be working directly with an experienced (and fun) team of brilliant people in a dynamic environment to grow the company that is revolutionizing the cloud computing world.
Responsibilities:
The Candidate would be tasked with solving a real-life business problem that requires processing/analysing TBs of data and handling variety of data sources
The candidate will be expected to deal with data extraction and munging, using appropriate ML techniques to build data science solutions and to implement these solutions in production.
The work is organized as a project with clear deliverables and stringent timelines
The Candidate would collaborate with other team members who would provide support and mentoring
The Candidate would proactively investigate, report, and where possible, address data quality issues Core
Skills:
Experience in using LLMs , both open source & proprietary models
Experience in building Q&A models using RAG , fine tuning LLMs - beyond prompt engineering techniques.
Experience in using tools like Langchain , LLamaIndex, vector databases is preferred Understanding of LLM Ops is a big plus
Strong SQL skills (6-7 Years of hands-on experience with complex queries and data munging)
Deep Machine Learning expertise (hands on with 6-7 years of experience)
Strong expertise in Python (particularly Machine Learning Libraries)
Experience implementing machine learning solutions in at least 3-5 real-life Analytics Projects (Excluding Academic/side projects)
Solid fundamentals, knowledge of supervised, unsupervised, machine learning and deep learning algorithms, such as classifiers, cluster analysis, dimension reduction, regression, time series forecasting, boosting/bagging, model explain ability techniques
Exposure to deep learning algorithms and areas such as NLP is a strong plus.
Excellent communication (written/verbal), presentation and facilitation skills
Ability to engage with business teams directly, especially with key stakeholders spread across different Geos (particularly AMER and EMEA)
Great presentation skills
Thanks & regards
Vivek Madari
Recruitement & Delivery Manager
vivek@fisecglobal.net
Location: Chicago IL (Hybrid Model) (3WFO/2WFH)
Duration: Long Term
The Analytics and Insights team is seeking a data scientist who loves working on complex problems and getting things done.
The ideal candidate combines excellent business acumen and communication skills with outstanding analytical skills. If you are detail-oriented, enjoy solving complex data challenges, and are passionate about data, we want to hear from you.
As a Data Scientist, you will work with data analysts, managers and engineers to: resolve ambiguity with data, play a crucial role in the iteration and optimization of analytics and ML products and support data-driven decision-making on a key project for the organization.
You'll be working directly with an experienced (and fun) team of brilliant people in a dynamic environment to grow the company that is revolutionizing the cloud computing world.
Responsibilities:
The Candidate would be tasked with solving a real-life business problem that requires processing/analysing TBs of data and handling variety of data sources
The candidate will be expected to deal with data extraction and munging, using appropriate ML techniques to build data science solutions and to implement these solutions in production.
The work is organized as a project with clear deliverables and stringent timelines
The Candidate would collaborate with other team members who would provide support and mentoring
The Candidate would proactively investigate, report, and where possible, address data quality issues Core
Skills:
Experience in using LLMs , both open source & proprietary models
Experience in building Q&A models using RAG , fine tuning LLMs - beyond prompt engineering techniques.
Experience in using tools like Langchain , LLamaIndex, vector databases is preferred Understanding of LLM Ops is a big plus
Strong SQL skills (6-7 Years of hands-on experience with complex queries and data munging)
Deep Machine Learning expertise (hands on with 6-7 years of experience)
Strong expertise in Python (particularly Machine Learning Libraries)
Experience implementing machine learning solutions in at least 3-5 real-life Analytics Projects (Excluding Academic/side projects)
Solid fundamentals, knowledge of supervised, unsupervised, machine learning and deep learning algorithms, such as classifiers, cluster analysis, dimension reduction, regression, time series forecasting, boosting/bagging, model explain ability techniques
Exposure to deep learning algorithms and areas such as NLP is a strong plus.
Excellent communication (written/verbal), presentation and facilitation skills
Ability to engage with business teams directly, especially with key stakeholders spread across different Geos (particularly AMER and EMEA)
Great presentation skills
Thanks & regards
Vivek Madari
Recruitement & Delivery Manager
vivek@fisecglobal.net
fisecglobal.net
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Frequently asked questions
Q: What skills or qualities help someone succeed as a HRIS Data Architect and Data Warehouse Developer?
A: To succeed as a HRIS Data Architect and Data Warehouse Developer, key technical skills include proficiency in data modeling, data warehousing tools such as ETL (Extract, Transform, Load) software, and programming languages like SQL, Python, or Java. Additionally, strong analytical, problem-solving, and communication skills are essential, as well as the ability to collaborate with stakeholders and technical teams to design and implement data solutions. These strengths enable HRIS Data Architects and Data Warehouse Developers to effectively manage complex data systems, drive business insights, and support organizational growth.
Q: What is the career path for a HRIS Data Architect and Data Warehouse Developer?
A: A typical career progression for a HRIS Data Architect and Data Warehouse Developer involves starting as a Data Analyst or Business Intelligence Developer, then advancing to a Data Architect or Senior Data Analyst role, and eventually becoming a Lead Data Architect or Enterprise Data Architect. Key opportunities for skill development include learning data governance, cloud-based data platforms, and advanced data visualization tools, as well as developing expertise in data modeling, data warehousing, and business intelligence. Long-term career prospects may include transitioning into executive roles such as Chief Data Officer or Chief Information Officer, or pursuing specialized roles like Data Scientist or Business Intelligence Manager.