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InfoVision Inc. · 7 hours ago

Data Scientist

Denver, CO

Contract

Onsite

Senior Level

InfoVision Inc. is seeking a Senior Data Science Consultant with deep experience in Data Science, DevOps/MLOps, and Data Visualization. The role involves architecting and delivering scalable data and ML solutions, leading cross-functional initiatives to improve system and API reliability, and building predictive models for forecasting failures.

Information Technology & Services

Growth Opportunities

H1B Sponsor Likely

Hiring Manager

Harsha Nagaraj

Responsibilities

Architect and deliver scalable, production‑grade data and ML solutions

Lead cross‑functional initiatives to improve system and API reliability

Build predictive models that forecast failures before they occur

Guide teams through complex troubleshooting and performance optimization

Influence technical strategy and engineering standards across the organization

Lead the design and execution of complex analytical frameworks to detect patterns, anomalies, and failure precursors

Conduct advanced EDA to uncover multi‑layer correlations across product, operational, and infrastructure datasets

Apply predictive modeling and machine learning to identify where system or API issues are most likely to occur

Use statistical process control and drift detection techniques to ensure ongoing operational stability

Build simulation and forecasting models to evaluate the impact of load changes, upgrades, or new features on system behavior

Establish and enforce best practices for reproducible research, model validation, and experimentation

Architect end‑to‑end observability solutions to track API latency, throughput, error rates, saturation, and SLO adherence

Build automated pipelines that ingest, aggregate, and model API telemetry logs and traces (OpenTelemetry, Prometheus, CloudWatch, Application Insights, etc.)

Detect and explain leading indicators of API instability using anomaly detection, time‑series forecasting, and multivariate correlation

Provide engineering with “risk heatmaps” to identify high‑risk services, endpoints, or infrastructure components

Design and implement predictive models that forecast outages, SLA breaches, or performance regressions

Develop automated early‑warning systems integrated into observability platforms

Architect proactive mitigation workflows: Adaptive scaling rules, Automated rollback/canary strategies, Circuit breakers and fault‑tolerance improvements, Predictive alerting thresholds

Architect and optimize CI/CD workflows for model deployment and data pipelines

Develop and maintain Docker/Kubernetes‑based services for training, inference, and analytics

Implement observability frameworks for ML workloads, ensuring traceability, logging, and performance monitoring

Maintain model registries, drift detection systems, and automated retraining strategies

Use IaC (Terraform/Bicep/CloudFormation) to maintain secure, reproducible environments

Design and optimize scalable ETL/ELT pipelines across batch and streaming architectures

Develop transformations, semantic layers, and feature stores supporting both predictive analytics and operational monitoring

Integrate API event logs, telemetry, and performance metrics into high‑quality analytics datasets

Establish data quality SLAs and automated validation processes

Build executive‑quality dashboards that communicate API health, KPIs, predictive signals, and operational trends

Create advanced visualizations: forecast bands, anomaly indicators, latency distributions, saturation patterns, and future‑state projections

Standardize visualization frameworks, semantic metrics, and documentation across teams

Influence decision‑making by translating predictive findings into clear, concise recommendations

Serve as a technical leader across engineering, driving standards for reliability, observability, and data‑driven decision‑making

Mentor engineers and data scientists, conducting code reviews, design reviews, and knowledge‑sharing sessions

Lead post‑incident reviews and guide teams in building lasting solutions, not short‑term patches

Partner with product and engineering leadership to define roadmaps, set metrics, and prioritize improvements

Communicate complex technical topics to executives with clarity and measurable impact

Champion a culture of quality, automation, performance excellence, and continuous improvement

Qualification

PythonSQLCI/CD pipelinesDocker/KubernetesData visualization toolsAPI performance toolsTime-series modelingObservability dataTroubleshootingMentorshipCollaborationTechnical leadership

Required

Senior‑level proficiency in Python, SQL, and software engineering best practices (testing, design patterns, modular architecture)

Extensive experience with observability data: logs, metrics, traces, service topology, and distributed systems behavior

Hands‑on experience with API performance tools (Grafana, Prometheus, Datadog, New Relic, Splunk, Azure Monitor, CloudWatch, etc.)

Strong understanding of SLOs, SLIs, latency percentiles, error budgets, traffic analysis, and capacity planning

Deep experience with CI/CD pipelines, Git‑based workflows, and automated deployments

Strong skills in Docker/Kubernetes and cloud-native microservice environments

Expertise in data visualization tools (Power BI, Tableau, Looker) and Python visualization libraries

Experience with time-series modeling, anomaly detection, and forecasting (ARIMA, Prophet, Holt‑Winters, LSTM, etc.)

Proven ability to troubleshoot complex, distributed system issues and drive long‑term resolutions

Demonstrated ability to own systems end‑to‑end through design, implementation, deployment, and maintenance

Preferred

Experience in system or API predictive modeling (e.g., Monte Carlo, reliability models)

Experience building risk scoring systems for performance, stability, or reliability

Familiarity with distributed tracing tools (OpenTelemetry, Jaeger, Zipkin)

Experience with SRE practices and incident‑response engineering

Experience with dbt, Airflow, Dagster, or Prefect for orchestration

Experience with MLflow, Databricks, SageMaker, Azure ML, or similar MLOps platforms

Ability to design automated mitigation strategies (predictive alerts, auto-scaling, failure‑prevention policies)

Experience influencing cross‑team architecture decisions in large, complex systems

Company

InfoVision Inc.

Glassdoor4.2

Infovision, founded in 1995, is a leading global IT services company offering enterprise digital transformation and modernization solutions across business verticals.

Founded in 1995

Richardson, TX, US

1001-5000 employees

https://www.infovision.com/

H1B Sponsorship

InfoVision Inc. has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

Represents job field similar to this job

Trends of Total Sponsorships

2025 (94)

2024 (59)

2023 (59)

2022 (72)

2021 (65)

2020 (90)