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Data Analytics Manager Jobs in Foley, AL (NOW HIRING)

The Analyst will assist project teams by preparing detailed reports, managing records retention ... Project Reporting & Data Analysis * Assist in tabulation, tracking, and development of critical ...

Data Intake Operator

Mobile, AL · On-site

$17.50 - $23.50/hr

Data Intake Operator CGI is seeking Data Intake Operator II to support critical data processing and ... This position requires strong analytical skills, attention to detail, and the ability to manage ...

SharePoint Developer

Mobile, AL · On-site

$48.50 - $63.50/hr

The ideal candidate will demonstrate proficiency in SharePoint architecture, workflow automation, dashboard creation, and data analytics to enable efficient program management and documentation ...

SharePoint Developer

Mobile, AL

$48.50 - $63.50/hr

The ideal candidate will demonstrate proficiency in SharePoint architecture, workflow automation, dashboard creation, and data analytics to enable efficient program management and documentation ...

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Data Analytics Manager information

See Foley, AL salary details

$26.5K

$83.1K

$147.2K

How much do data analytics manager jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data analytics manager in Foley, AL is $83,137.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,500.00 and $107,400.00 per year, depending on experience, location, and employer.

Will AI replace a data analyst?

AI tools can automate routine data processing and basic analysis tasks, but the role of a data analyst involves interpreting complex data, providing insights, and communicating findings, which require human judgment and domain expertise. Therefore, while AI may augment certain responsibilities, it is unlikely to fully replace data analysts in the near future, and skills in data storytelling and critical thinking remain essential.

How do Data Analytics Managers typically collaborate with stakeholders from non-technical departments?

Data Analytics Managers often act as a bridge between technical data teams and non-technical stakeholders, such as marketing, finance, or operations. They translate complex data insights into actionable recommendations and ensure that analyses align with business objectives. Regular communication, tailored presentations, and workshops are common practices to ensure all stakeholders understand the value and limitations of analytical findings. This collaborative approach helps drive data-driven decision-making across the organization.

What does a data analyst manager do?

A data analyst manager oversees a team of data analysts, guiding data collection, analysis, and reporting to support business decision-making. They develop strategies, ensure data accuracy, and often use tools like SQL, Excel, or data visualization software to interpret complex data sets. Strong leadership, communication skills, and knowledge of analytics tools are essential for this role.

How much do data analytics managers make?

Data analytics managers in the US typically earn a median salary of around $100,000 to $130,000 annually, with experienced professionals and those in high-demand industries earning higher. Salaries can vary based on location, education, certifications, and company size, and many roles require proficiency in tools like SQL, Python, or Tableau.

What are the key skills and qualifications needed to thrive as a Data Analytics Manager, and why are they important?

To thrive as a Data Analytics Manager, you need strong analytical skills, expertise in statistical methods, and a background in data science or a related field, often supported by a bachelor's or master's degree. Proficiency with data visualization tools (such as Tableau or Power BI), SQL, and analytics platforms like Python or R is typically required, along with experience in managing data projects. Leadership, strategic thinking, and effective communication are important soft skills for leading teams and translating data insights into actionable business strategies. These skills ensure that analytical initiatives drive business value and support informed decision-making across the organization.

What does a Data Analytics Manager do?

A Data Analytics Manager oversees data analysis operations and leads a team of analysts to extract actionable insights from data. They are responsible for managing data-driven projects, ensuring data integrity, and presenting findings to help guide business decisions. Their role often involves collaborating with various departments, setting analytic strategies, and ensuring that the team uses the most effective tools and methodologies. Additionally, they may handle hiring, training, and performance reviews of analytics staff.

What is the difference between Data Analytics Manager vs Data Analyst?

AspectData Analytics ManagerData Analyst
ResponsibilitiesOversees analytics projects, manages teams, develops strategiesPerforms data collection, cleaning, and analysis to generate reports
Required SkillsLeadership, project management, advanced analyticsData manipulation, statistical analysis, visualization
QualificationsBachelor's or Master's in Data Science, Analytics, or related fields; certifications like CAP or Microsoft Certified Data AnalystBachelor's in Statistics, Mathematics, or related fields; certifications like Microsoft Certified Data Analyst
Work EnvironmentCorporate offices, analytics teams, cross-department collaborationData teams, business units, often in office or remote settings

In summary, a Data Analytics Manager leads analytics teams and strategies, requiring leadership skills and advanced certifications, while a Data Analyst focuses on data processing and reporting, with more technical and analytical tasks. Both roles are essential in data-driven organizations and often work closely together.

Is a data analyst a high salary?

Data analysts typically earn moderate to high salaries depending on experience, industry, and location. While entry-level positions may have lower pay, experienced data analysts with skills in SQL, Excel, and data visualization tools can command higher salaries, especially in competitive markets.
What cities near Foley, AL are hiring for Data Analytics Manager jobs? Cities near Foley, AL with the most Data Analytics Manager job openings:

Robotics Data Pipeline Engineer - Multimodal Data

Persona AI

Pensacola, FL • On-site

$108K - $130K/yr

Full-time

Medical, PTO

Re-posted 29 days ago


Job description

Job Title: Robotics Data Pipeline Engineer - Multimodal Data
Department: Software
Reports To: Teleoperations Lead
Employment Type: Full-Time
Location: Houston, TX or Pensacola Fl
Who We Are
Persona AI is building humanoid robots for the most demanding environments in heavy industry - shipyards, steel mills, fabrication facilities, and offshore platforms - performing welding, grinding, maintenance, inspection, and material-handling work that is dangerous, physically demanding, and increasingly difficult to staff.
We are backed by leading strategic and financial investors and engaged with global industrial leaders across Korea, Japan, the United States, and Singapore. Korea is the center of gravity for our early commercial strategy, anchored by relationships with the world's leading shipbuilders and steelmakers. Our work spans both the robot platform itself and the systems, partners, and playbooks required to deploy it at scale.
Why Join Persona AI?
  • We offer competitive compensation, a performance-based bonus, 99% employer covered medical benefits, early-stage equity, competitive PTO, and a company-wide paid winter break between December 24th and January 2nd.
  • You'll shape technology that's redefining the possibilities of robotics and human interaction.
  • Work alongside passionate teammates who value creativity, and continuous learning.
  • Enjoy full access to advanced tools,

About the Role
As a Data Pipeline Engineer, you will architect and scale the data infrastructure that feeds our foundation models. Your primary mission is to extract, augment, and align human dexterous manipulation data from massive complex, multi-sensor and egocentric video datasets. Crucially, you will build advanced post-processing algorithms to perform deep force analysis and infer hidden states from raw data-such as processing direct force-torque outputs to quantify grasp dynamics, estimating contact forces from visual cues, extrapolating heavily occluded hand positions, or deriving 3D geometry from 2D frames. You will use spatial, temporal, and cross-modal data augmentation to multiply the value of every minute of data our teleoperation team collects.
What You Will Be Doing
  • Multimodal Data Pipelines: Architect end-to-end ingestion pipelines that take raw, unstructured recordings-egocentric video, teleoperation sessions, third-party open datasets-and produce indexed, queryable, training-ready datasets. This includes temporal segmentation of long recordings into action clips, metadata and scene-graph extraction, embedding-based retrieval, and language annotation workflows.
  • Force Analysis & Hidden State Inference: Design cross-modal validation systems that verify video, proprioception, force/haptic signals, and language annotations agree with each other-e.g., reprojecting robot state into the image plane to confirm video-state consistency, and VLM-assisted checks that instructions match observed behavior.
  • Kinematic Retargeting & Alignment: orchestrating hand-tracking, segmentation, depth estimation, 3D reconstruction, and pose-tracking modules; retargeting human demonstrations into robot trajectories; and running simulation-in-the-loop validation (kinematic feasibility, physics replay, motion-consistency filtering) so synthesized data is physically grounded, not just visually plausible.
  • Advanced Data Augmentation: Implement robust data augmentation strategies (spatial transformations, temporal scaling, synthetic viewpoints, and sensor noise injection) to expand expert trajectories and improve the robustness of our learning models.
  • Teleoperation Synchronization: unified state-action representations across differing embodiments, coordinate frames, rotation conventions, gripper/hand parameterizations, and sampling rates-with per-dimension validity masking and per-source normalization so that adding a new robot or sensor is a configuration change, not a rewrite.
  • Close the loop with data consumers: build the tooling that lets researchers query, visualize, and audit datasets (clip browsers, trajectory viewers, annotation review UIs), and turn model-failure analyses into new curation rules and targeted re-collection requests.

What We Are Looking For
  • Education: M.S., or Ph.D. in Computer Science, Data Engineering, Machine Learning, Robotics, Mechanical Engineering, or a related field.
  • Programming & ML Frameworks: Deep expertise in Python and extensive experience with PyTorch, specifically in handling custom dataloaders for multimodal datasets.
  • Force & Time-Series Data Processing: Experience analyzing and processing complex time-series data from force-torque (F/T) sensors, load cells, or tactile arrays, ensuring pristine alignment with visual frames.
  • Video Processing Expertise: Mastery of video processing pipelines and libraries (OpenCV, FFmpeg, Decord) and managing the I/O bottlenecks of terabyte-scale video datasets.
  • Solid working knowledge of 3D geometry and robotics data: coordinate frames and transforms, rotation representations, camera intrinsics/extrinsics, forward/inverse kinematics, URDF-enough to build automated checks that catch geometric inconsistencies in the data.
  • Data Augmentation: Proven ability to implement programmatic and generative data augmentation techniques for computer vision and time-series data.

Bonus Skills
  • Experience with NVIDIA's robotic software stack (Open X-Embodiment, DROID, AgiBot World, EgoDex, or similar).
  • Familiarity with the modern perception toolbox as a user: segmentation (SAM-family), monocular depth, hand/body pose estimation (MANO/SMPL), 6-DoF object pose tracking, point tracking-you don't need to train these models, but you should be comfortable composing and evaluating them in a pipeline
  • Familiarity with distributed data processing systems (Ray, Apache Spark) for cluster computing.
  • Background in generating or utilizing synthetic robotic data via simulation (Omniverse, MuJoCo).
  • Experience integrating spatial awareness or tactile data representations (e.g., Fourier encoding) into visual pipelines.

Persona AI is an Equal Opportunity Employer.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability, veteran status, or any other characteristic protected by applicable federal, state, or local law.